Alternatives to Altada
Compare Altada alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Altada in 2026. Compare features, ratings, user reviews, pricing, and more from Altada competitors and alternatives in order to make an informed decision for your business.
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Kylo
Teradata
Kylo is an open source enterprise-ready data lake management software platform for self-service data ingest and data preparation with integrated metadata management, governance, security and best practices inspired by Think Big's 150+ big data implementation projects. Self-service data ingest with data cleansing, validation, and automatic profiling. Wrangle data with visual sql and an interactive transform through a simple user interface. Search and explore data and metadata, view lineage, and profile statistics. Monitor health of feeds and services in the data lake. Track SLAs and troubleshoot performance. Design batch or streaming pipeline templates in Apache NiFi and register with Kylo to enable user self-service. Organizations can expend significant engineering effort moving data into Hadoop yet struggle to maintain governance and data quality. Kylo dramatically simplifies data ingest by shifting ingest to data owners through a simple guided UI. -
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Onehouse
Onehouse
The only fully managed cloud data lakehouse designed to ingest from all your data sources in minutes and support all your query engines at scale, for a fraction of the cost. Ingest from databases and event streams at TB-scale in near real-time, with the simplicity of fully managed pipelines. Query your data with any engine, and support all your use cases including BI, real-time analytics, and AI/ML. Cut your costs by 50% or more compared to cloud data warehouses and ETL tools with simple usage-based pricing. Deploy in minutes without engineering overhead with a fully managed, highly optimized cloud service. Unify your data in a single source of truth and eliminate the need to copy data across data warehouses and lakes. Use the right table format for the job, with omnidirectional interoperability between Apache Hudi, Apache Iceberg, and Delta Lake. Quickly configure managed pipelines for database CDC and streaming ingestion. -
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Utelly
Synamedia Utelly
Metadata aggregation, AI/ML enrichments, search & recommendation APIs, CMS, and promotion engine: Utelly brings the best content discovery toolkit for TV & OTT clients. We ingest core metadata catalogs to provide a universal view of the content available, along with ingesting individual feeds which are matched with the core metadata to provide an enriched unified dataset ready for powering content discovery. Our AI enrichment modules allow sparse data sets to be enhanced and then used to achieve improved content discovery experiences. Our search can be indexed on individual catalogs or a universal dataset, to provide an entertainment-focused search capability which is a future-proof approach to providing your customers with a great search experience. Our powerful recommendation engine leverages the latest ML/AI techniques to generate personalized recommendations based on key indicators identified throughout a user life cycle along with ingesting datasets.Starting Price: Free -
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Apache Doris
The Apache Software Foundation
Apache Doris is a modern data warehouse for real-time analytics. It delivers lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within a second. Storage engine with real-time upsert, append and pre-aggregation. Optimize for high-concurrency and high-throughput queries with columnar storage engine, MPP architecture, cost based query optimizer, vectorized execution engine. Federated querying of data lakes such as Hive, Iceberg and Hudi, and databases such as MySQL and PostgreSQL. Compound data types such as Array, Map and JSON. Variant data type to support auto data type inference of JSON data. NGram bloomfilter and inverted index for text searches. Distributed design for linear scalability. Workload isolation and tiered storage for efficient resource management. Supports shared-nothing clusters as well as separation of storage and compute.Starting Price: Free -
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The Qlik Data Integration platform for managed data lakes automates the process of providing continuously updated, accurate, and trusted data sets for business analytics. Data engineers have the agility to quickly add new sources and ensure success at every step of the data lake pipeline from real-time data ingestion, to refinement, provisioning, and governance. A simple and universal solution for continually ingesting enterprise data into popular data lakes in real-time. A model-driven approach for quickly designing, building, and managing data lakes on-premises or in the cloud. Deliver a smart enterprise-scale data catalog to securely share all of your derived data sets with business users.
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Electrik.Ai
Electrik.Ai
Automatically ingest marketing data into any data warehouse or cloud file storage of your choice such as BigQuery, Snowflake, Redshift, Azure SQL, AWS S3, Azure Data Lake, Google Cloud Storage with our fully managed ETL pipelines in the cloud. Our hosted marketing data warehouse integrates all your marketing data and provides ad insights, cross-channel attribution, content insights, competitor Insights, and more. Our customer data platform performs identity resolution in real-time across data sources thus enabling a unified view of the customer and their journey. Electrik.AI is a cloud-based marketing analytics software and full-service platform. Electrik.AI’s Google Analytics Hit Data Extractor enriches and extracts the un-sampled hit level data sent to Google Analytics from the website or application and periodically ships it to your desired destination database/data warehouse or file/data lake.Starting Price: $49 per month -
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Hydrolix
Hydrolix
Hydrolix is a streaming data lake that combines decoupled storage, indexed search, and stream processing to deliver real-time query performance at terabyte-scale for a radically lower cost. CFOs love the 4x reduction in data retention costs. Product teams love 4x more data to work with. Spin up resources when you need them and scale to zero when you don’t. Fine-tune resource consumption and performance by workload to control costs. Imagine what you can build when you don’t have to sacrifice data because of budget. Ingest, enrich, and transform log data from multiple sources including Kafka, Kinesis, and HTTP. Return just the data you need, no matter how big your data is. Reduce latency and costs, eliminate timeouts, and brute force queries. Storage is decoupled from ingest and query, allowing each to independently scale to meet performance and budget targets. Hydrolix’s high-density compression (HDX) typically reduces 1TB of stored data to 55GB.Starting Price: $2,237 per month -
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Cazena
Cazena
Cazena’s Instant Data Lake accelerates time to analytics and AI/ML from months to minutes. Powered by its patented automated data platform, Cazena delivers the first SaaS experience for data lakes. Zero operations required. Enterprises need a data lake that easily supports all of their data and tools for analytics, machine learning and AI. To be effective, a data lake must offer secure data ingestion, flexible data storage, access and identity management, tool integration, optimization and more. Cloud data lakes are complicated to do yourself, which is why they require expensive teams. Cazena’s Instant Cloud Data Lakes are instantly production-ready for data loading and analytics. Everything is automated, supported on Cazena’s SaaS Platform with continuous Ops and self-service access via the Cazena SaaS Console. Cazena's Instant Data Lakes are turnkey and production-ready for secure data ingest, storage and analytics. -
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Fortanix Confidential AI
Fortanix
Fortanix Confidential AI is a unified platform that enables data teams to process sensitive datasets and run AI/ML models entirely within confidential computing environments, combining managed infrastructure, software, and workflow orchestration to maintain organizational privacy compliance. The service offers readily available, on-demand infrastructure powered by Intel Ice Lake third-generation scalable Xeon processors and supports execution of AI frameworks inside Intel SGX and other enclave technologies with zero external visibility. It delivers hardware-backed proofs of execution and detailed audit logs for stringent regulatory requirements, secures every stage of the MLOps pipeline, from data ingestion via Amazon S3 connectors or local uploads through model training, inference, and fine-tuning, and provides broad model compatibility. -
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Arthur AI
Arthur
Track model performance to detect and react to data drift, improving model accuracy for better business outcomes. Build trust, ensure compliance, and drive more actionable ML outcomes with Arthur’s explainability and transparency APIs. Proactively monitor for bias, track model outcomes against custom bias metrics, and improve the fairness of your models. See how each model treats different population groups, proactively identify bias, and use Arthur's proprietary bias mitigation techniques. Arthur scales up and down to ingest up to 1MM transactions per second and deliver insights quickly. Actions can only be performed by authorized users. Individual teams/departments can have isolated environments with specific access control policies. Data is immutable once ingested, which prevents manipulation of metrics/insights. -
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Inspira Machine Suite
Inspira
Inspira’s Machine Suite consists of several AI-enabled ‘engines’ that can be customized by our team to perform hundreds of routine management tasks…tasks that are time-consuming for humans, but trivial for the machine suite. Each engine seamlessly integrates to autonomously optimize production levels. Data can also be ingested from any AI production tool that has been integrated with the machine, via our API. (Custom endpoints are available upon request.) The classification engine classifies, labels and stores data on encrypted AWS servers in a format the other AI engines can process. After ingest, the data is cleaned, normalized, enriched and aggregated in preparation for additional processing by other engines of the machine. -
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Data Lakes on AWS
Amazon
Many Amazon Web Services (AWS) customers require a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is a new and increasingly popular way to store and analyze data because it allows companies to manage multiple data types from a wide variety of sources, and store this data, structured and unstructured, in a centralized repository. The AWS Cloud provides many of the building blocks required to help customers implement a secure, flexible, and cost-effective data lake. These include AWS managed services that help ingest, store, find, process, and analyze both structured and unstructured data. To support our customers as they build data lakes, AWS offers the data lake solution, which is an automated reference implementation that deploys a highly available, cost-effective data lake architecture on the AWS Cloud along with a user-friendly console for searching and requesting datasets. -
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Apache DevLake
Apache Software Foundation
Apache DevLake (Incubating) ingests, analyzes, and visualizes the fragmented data from DevOps tools to distill insights for engineering excellence. Your data lives in many silos and tools. DevLake brings them all together to give you a complete view of your Software Development Life Cycle (SDLC). From DORA to scrum retros, DevLake implements metrics effortlessly with prebuilt dashboards supporting common frameworks and goals. DevLake fits teams of all shapes and sizes, and can be readily extended to support new data sources, metrics, and dashboards, with a flexible framework for data collection and transformation. Select, transform and set up a schedule for the data you wish to sync from your prefered data sources in the config UI. View pre-built dashboards of a variety of use cases and learn engineering insights from the metrics. Customize your own metrics or dashboards with SQL to extend your usage of DevLake.Starting Price: Free -
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Qlik Compose
Qlik
Qlik Compose for Data Warehouses provides a modern approach by automating and optimizing data warehouse creation and operation. Qlik Compose automates designing the warehouse, generating ETL code, and quickly applying updates, all whilst leveraging best practices and proven design patterns. Qlik Compose for Data Warehouses dramatically reduces the time, cost and risk of BI projects, whether on-premises or in the cloud. Qlik Compose for Data Lakes automates your data pipelines to create analytics-ready data sets. By automating data ingestion, schema creation, and continual updates, organizations realize faster time-to-value from their existing data lake investments. -
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Lentiq
Lentiq
Lentiq is a collaborative data lake as a service environment that’s built to enable small teams to do big things. Quickly run data science, machine learning and data analysis at scale in the cloud of your choice. With Lentiq, your teams can ingest data in real time and then process, clean and share it. From there, Lentiq makes it possible to build, train and share models internally. Simply put, data teams can collaborate with Lentiq and innovate with no restrictions. Data lakes are storage and processing environments, which provide ML, ETL, schema-on-read querying capabilities and so much more. Are you working on some data science magic? You definitely need a data lake. In the Post-Hadoop era, the big, centralized data lake is a thing of the past. With Lentiq, we use data pools, which are multi-cloud, interconnected mini-data lakes. They work together to give you a stable, secure and fast data science environment. -
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BryteFlow
BryteFlow
BryteFlow builds the most efficient automated environments for analytics ever. It converts Amazon S3 into an awesome analytics platform by leveraging the AWS ecosystem intelligently to deliver data at lightning speeds. It complements AWS Lake Formation and automates the Modern Data Architecture providing performance and productivity. You can completely automate data ingestion with BryteFlow Ingest’s simple point-and-click interface while BryteFlow XL Ingest is great for the initial full ingest for very large datasets. No coding is needed! With BryteFlow Blend you can merge data from varied sources like Oracle, SQL Server, Salesforce and SAP etc. and transform it to make it ready for Analytics and Machine Learning. BryteFlow TruData reconciles the data at the destination with the source continually or at a frequency you select. If data is missing or incomplete you get an alert so you can fix the issue easily. -
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1Data
Sincera
1Data is a modern, flexible data management platform that enables businesses to integrate, analyze, and act on data through low-code/no-code tools. It helps break down data silos, ingesting data from multiple sources via connectors (databases, APIs, files, messages), and lets users define business rules and workflows to automate analysis and trigger actions. Components include connectors, rules, workflows, a data dictionary, exception management, and metrics. Users can build simple or complex flows of data/events/rules to achieve specific outcomes, track what data exists and how it’s used via the data dictionary, and monitor, manage, or resolve data exceptions. 1Data also supports use cases like ETL/data pipelines, data lakes/warehouses, data standardization, reconciliation and cleansing, and data distribution. -
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Strike48
Strike48
Strike48 is the Agentic Operations Platform combining complete log visibility with customizable AI agents that run security, IT, and compliance operations at machine speed. Most organizations monitor only about 60-70% of their environment because traditional SIEM and observability platforms make full log coverage cost-prohibitive. Strike48 closes that visibility gap with architecture that decouples storage from upfront parsing decisions, letting teams ingest and retain all their logs without breaking budgets. Bring your logs or query them where they already live (Splunk, data lakes, cloud, on-prem), no rip-and-replace required. On top of that unified data layer, Strike48 deploys autonomous AI agents that run investigations, correlate and triage alerts, collect evidence, generate and validate detection rules, and hand work off to each other. A human-in-the-loop model ensures people approve critical actions like endpoint isolation and remediation, with full audit trails. -
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NVISIONx
NVISIONx
NVISIONx data risk Intelligence platform enables companies to gain control of their enterprise data to reduce data risks, compliance scopes, and storage costs. Data is growing out of control and getting worse every day. Business and security leaders are overwhelmed and can’t protect what they don’t know. More controls won’t fix the problem. Rich and unlimited analysis to support over 150 business use cases to empower data owners and cyber professionals to proactively manage their data from cradle to grave. First, categorize or group data that is redundant, outdated, or trivial (ROT) and see what data can be defensibly disposed of to reduce the classification scope (and storage costs). Then, contextually classify all remaining data using a number of easy-to-use data analytics techniques to enable the data owner to be their own data analyst! Data identified as useless and unwanted can then go through legal and records retention reviews. -
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Crux
Crux
Find out why the heavy hitters are using the Crux external data automation platform to scale external data integration, transformation, and observability without increasing headcount. Our cloud-native data integration technology accelerates the ingestion, preparation, observability and ongoing delivery of any external dataset. The result is that we can ensure you get quality data in the right place, in the right format when you need it. Leverage automatic schema detection, delivery schedule inference, and lifecycle management to build pipelines from any external data source quickly. Enhance discoverability throughout your organization through a private catalog of linked and matched data products. Enrich, validate, and transform any dataset to quickly combine it with other data sources and accelerate analytics. -
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CORAS’ Enterprise Decision Management Platform (EDMP) is a robust and scalable 360° Commercial-Off-The Shelf (COTS) application developed for DOD and Federal Agencies which ingests and/or integrates disparate sources of data (public or private) and presents it in a "single pane of glass" to facilitate decision management. Leveraging a proprietary data connection framework, APIs, and data lake, disparate data is ingested, transformed via ETL (Extract, Transform, Load), and rendered in a set of decision management tools permitting selections to be made in real-time. CORAS provides a frictionless platform to the DoD, tackling their major programming and asset management challenges through the aggregation of existing data sources, the analysis of project and program readiness, and the automation of information reporting. The resulting time savings can be measured in man-hours, decreasing the time to decision while also supplying historical records why decisions were made.
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Cribl Lake
Cribl
Storage that doesn’t lock data in. Get up and running fast with a managed data lake. Easily store, access, and retrieve data, without being a data expert. Cribl Lake keeps you from drowning in data. Easily store, manage, enforce policy on, and access data when you need. Dive into the future with open formats and unified retention, security, and access control policies. Let Cribl handle the heavy lifting so data can be usable and valuable to the teams and tools that need it. Minutes, not months to get up and running with Cribl Lake. Zero configuration with automated provisioning and out-of-the-box integrations. Streamline workflows with Stream and Edge for powerful data ingestion and routing. Cribl Search unifies queries no matter where data is stored, so you can get value from data without delays. Take an easy path to collect and store data for long-term retention. Comply with legal and business requirements for data retention by defining specific retention periods. -
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Dremio
Dremio
Dremio delivers lightning-fast queries and a self-service semantic layer directly on your data lake storage. No moving data to proprietary data warehouses, no cubes, no aggregation tables or extracts. Just flexibility and control for data architects, and self-service for data consumers. Dremio technologies like Data Reflections, Columnar Cloud Cache (C3) and Predictive Pipelining work alongside Apache Arrow to make queries on your data lake storage very, very fast. An abstraction layer enables IT to apply security and business meaning, while enabling analysts and data scientists to explore data and derive new virtual datasets. Dremio’s semantic layer is an integrated, searchable catalog that indexes all of your metadata, so business users can easily make sense of your data. Virtual datasets and spaces make up the semantic layer, and are all indexed and searchable. -
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Second State
Second State
Fast, lightweight, portable, rust-powered, and OpenAI compatible. We work with cloud providers, especially edge cloud/CDN compute providers, to support microservices for web apps. Use cases include AI inference, database access, CRM, ecommerce, workflow management, and server-side rendering. We work with streaming frameworks and databases to support embedded serverless functions for data filtering and analytics. The serverless functions could be database UDFs. They could also be embedded in data ingest or query result streams. Take full advantage of the GPUs, write once, and run anywhere. Get started with the Llama 2 series of models on your own device in 5 minutes. Retrieval-argumented generation (RAG) is a very popular approach to building AI agents with external knowledge bases. Create an HTTP microservice for image classification. It runs YOLO and Mediapipe models at native GPU speed. -
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NewEvol
Sattrix Software Solutions
NewEvol is the technologically advanced product suite that uses data science for advanced analytics to identify abnormalities in the data itself. Supported by visualization, rule-based alerting, automation, and responses, NewEvol becomes a more compiling proposition for any small to large enterprise. Machine Learning (ML) and security intelligence feed makes NewEvol a more robust system to cater to challenging business demands. NewEvol Data Lake is super easy to deploy and manage. You don’t require a team of expert data administrators. As your company’s data need grows, it automatically scales and reallocates resources accordingly. NewEvol Data Lake has extensive data ingestion to perform enrichment across multiple sources. It helps you ingest data from multiple formats such as delimited, JSON, XML, PCAP, Syslog, etc. It offers enrichment with the help of a best-of-breed contextually aware event analytics model. -
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Kloudfuse
Kloudfuse
Kloudfuse is an AI‑powered unified observability platform that scales cost‑effectively, combining metrics, logs, traces, events, and digital experience monitoring into a single observability data lake. It integrates with over 700 sources, agent‑based or open source, without re‑instrumentation, and supports open query languages like PromQL, LogQL, TraceQL, GraphQL, and SQL while enabling custom workflows through webhooks and notifications. Organizations can deploy Kloudfuse within their VPC using a simple single‑command install and manage it centrally via a control plane. It automatically ingests and indexes telemetry data with intelligent facets, enabling fast search, context‑aware ML‑based alerts, and SLOs with reduced false positives. Users gain full‑stack visibility, from frontend RUM and session replays to backend profiling, traces, and metrics, allowing navigation from user experience down to code‑level issues. -
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Infor Data Lake
Infor
Solving today’s enterprise and industry challenges requires big data. The ability to capture data from across your enterprise—whether generated by disparate applications, people, or IoT infrastructure–offers tremendous potential. Infor’s Data Lake tools deliver schema-on-read intelligence along with a fast, flexible data consumption framework to enable new ways of making key decisions. With leveraged access to your entire Infor ecosystem, you can start capturing and delivering big data to power your next generation analytics and machine learning strategies. Infinitely scalable, the Infor Data Lake provides a unified repository for capturing all of your enterprise data. Grow with your insights and investments, ingest more content for better informed decisions, improve your analytics profiles, and provide rich data sets to build more powerful machine learning processes. -
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Ragie
Ragie
Ragie streamlines data ingestion, chunking, and multimodal indexing of structured and unstructured data. Connect directly to your own data sources, ensuring your data pipeline is always up-to-date. Built-in advanced features like LLM re-ranking, summary index, entity extraction, flexible filtering, and hybrid semantic and keyword search help you deliver state-of-the-art generative AI. Connect directly to popular data sources like Google Drive, Notion, Confluence, and more. Automatic syncing keeps your data up-to-date, ensuring your application delivers accurate and reliable information. With Ragie connectors, getting your data into your AI application has never been simpler. With just a few clicks, you can access your data where it already lives. Automatic syncing keeps your data up-to-date ensuring your application delivers accurate and reliable information. The first step in a RAG pipeline is to ingest the relevant data. Use Ragie’s simple APIs to upload files directly.Starting Price: $500 per month -
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LlamaCloud
LlamaIndex
LlamaCloud, developed by LlamaIndex, is a fully managed service for parsing, ingesting, and retrieving data, enabling companies to create and deploy AI-driven knowledge applications. It provides a flexible and scalable pipeline for handling data in Retrieval-Augmented Generation (RAG) scenarios. LlamaCloud simplifies data preparation for LLM applications, allowing developers to focus on building business logic instead of managing data. -
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SingleStore
SingleStore
SingleStore (formerly MemSQL) is a distributed, highly-scalable SQL database that can run anywhere. We deliver maximum performance for transactional and analytical workloads with familiar relational models. SingleStore is a scalable SQL database that ingests data continuously to perform operational analytics for the front lines of your business. Ingest millions of events per second with ACID transactions while simultaneously analyzing billions of rows of data in relational SQL, JSON, geospatial, and full-text search formats. SingleStore delivers ultimate data ingestion performance at scale and supports built in batch loading and real time data pipelines. SingleStore lets you achieve ultra fast query response across both live and historical data using familiar ANSI SQL. Perform ad hoc analysis with business intelligence tools, run machine learning algorithms for real-time scoring, perform geoanalytic queries in real time.Starting Price: $0.69 per hour -
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RushDB
RushDB
RushDB is an open-source zero-configuration graph database that instantly transforms JSON and CSV into a fully normalized, queryable Neo4j graph - without the overhead of schema design, migrations, or manual indexing. Designed for modern applications, AI, and ML workflows, RushDB provides a frictionless developer experience, combining the flexibility of NoSQL with the structured power of relational databases. With automatic data normalization, ACID compliance, and a powerful API, RushDB eliminates the complexities of data ingestion, relationship management, and query optimization - so you can focus on building, not database administration. Key Features: 1. Zero Configuration, Instant Data Ingestion 2. Graph-Powered Storage & Queries 3. ACID Transactions & Schema Evolution 4. Developer-Centric API: Query Like an SDK 5. High-Performance Search & Analytics 6. Self-Hosted or Cloud-ReadyStarting Price: $9/month -
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Progress Agentic RAG
Progress Software
Progress Agentic RAG is a SaaS Retrieval-Augmented Generation platform that automatically indexes, searches, and generates AI-powered insights from structured and unstructured business data, including documents, emails, video, slides, and more, by combining RAG with agentic workflows that reason, classify, summarize, and answer queries with traceable, verifiable results without requiring users to build and manage their own RAG infrastructure. Designed as a modular no-code RAG-as-a-Service solution, it accelerates AI readiness by letting organizations extract contextual intelligence and business knowledge using natural language queries and quality-driven output metrics while integrating with any leading Large Language Model (LLM) and supporting multilingual, multimodal content indexing and retrieval. Features include AI summarization and classification, generated Q&A from enterprise data, a Prompt Lab for validating LLM behavior with custom prompts.Starting Price: $700 per month -
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Peaka
Peaka
Integrate all your data sources, relational and NoSQL databases, SaaS tools, and APIs. Query them as a single data source immediately. Process data wherever it is. Query, cache, and blend data from different sources. Use webhooks to ingest streaming data from Kafka, Segment, etc., into the Peaka BI Table. Replace nightly one-time batch ingestion with real-time data access. Treat every data source like a relational database. Convert any API to a table, and blend and join it with your other data sources. Use the familiar SQL to run queries in NoSQL databases. Retrieve data from both SQL and NoSQL databases utilizing the same skill set. Query and filter your consolidated data to form new data sets. Expose them with APIs to serve other apps and systems. Do not get bogged down in scripts and logs while setting up your data stack. Eliminate the burden of building, managing, and maintaining ETL pipelines.Starting Price: $1 per month -
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Imply
Imply
Imply is a real-time analytics platform built on Apache Druid, designed to handle large-scale, high-performance OLAP (Online Analytical Processing) workloads. It offers real-time data ingestion, fast query performance, and the ability to perform complex analytical queries on massive datasets with low latency. Imply is tailored for organizations that need interactive analytics, real-time dashboards, and data-driven decision-making at scale. It provides a user-friendly interface for data exploration, along with advanced features such as multi-tenancy, fine-grained access controls, and operational insights. With its distributed architecture and scalability, Imply is well-suited for use cases in streaming data analytics, business intelligence, and real-time monitoring across industries. -
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Bluemetrix
Bluemetrix
Migrating data to the cloud is difficult. Let us simplify the process for you with Bluemetrix Data Manager (BDM). BDM automates the ingestion of complex data sources and ensures that as your data sources change dynamically, your pipelines configure automatically to match the new data sources. BDM provides the application of automation and processing of data at scale, in a secure modern environment, with smart GUI and API interfaces available. With data governance fully automated, it is now possible to streamline pipeline creation, while recording and storing all actions automatically in your catalogue as the pipeline executes. Easy to create templating, combined with smart scheduling options, enables Self Service capability for data consumers - both business and technical users. A free enterprise-grade data ingestion tool that will automate the ingestion of data smoothly and quickly from on-premise sources into the cloud, while also automating the creation and running of pipelines. -
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RediSearch
Redis
Redis Enterprise includes a powerful real-time indexing, querying, and full-text search engine available on-premises and as a managed service in the cloud. Redis real-time search supports fast indexing and ingestion. It’s engineered for performance using in-memory data structures implemented in C. Scale out and partition indexes over several shards and nodes for greater speed and memory capacity. Enjoy continued operations in any scenario with five-nines availability and Active-Active failover. Redis Enterprise real-time search allows you to quickly create primary and secondary indexes on Hash and JSON datasets using an incremental indexing approach for fast index creation and deletion. The indexes let you query data at top speed, perform complex aggregations, filter by properties, numeric ranges as well as geographical distance. -
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OpenText Security Log Analytics
OpenText
OpenText™ Security Log Analytics is a scalable and user-friendly security operations platform designed to accelerate threat detection through comprehensive log management and big data analytics. It features a natural language-like querying interface that simplifies complex data searches, enabling security teams to visualize and analyze security events quickly and efficiently. The core columnar database ensures data immutability, enhancing trust and integrity in log management. This solution helps reduce analyst fatigue by streamlining threat hunting processes and automating repetitive remediation tasks. Integrated compliance reporting supports audit readiness for standards like GDPR, PCI, and FIPS 140-2. It also supports data ingestion from over 480 sources, providing a unified and normalized view for enhanced security visibility. -
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Varada
Varada
Varada’s dynamic and adaptive big data indexing solution enables to balance performance and cost with zero data-ops. Varada’s unique big data indexing technology serves as a smart acceleration layer on your data lake, which remains the single source of truth, and runs in the customer cloud environment (VPC). Varada enables data teams to democratize data by operationalizing the entire data lake while ensuring interactive performance, without the need to move data, model or manually optimize. Our secret sauce is our ability to automatically and dynamically index relevant data, at the structure and granularity of the source. Varada enables any query to meet continuously evolving performance and concurrency requirements for users and analytics API calls, while keeping costs predictable and under control. The platform seamlessly chooses which queries to accelerate and which data to index. Varada elastically adjusts the cluster to meet demand and optimize cost and performance. -
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SpectX
SpectX
SpectX is a powerful log analyzer for incident investigation and data exploration. It does not ingest or index data but runs queries directly on log files stored in file systems or blob storage. Local log servers, cloud storage, Hadoop clusters, JDBC-databases, production servers, Elastic clusters, or anything that speaks HTTP - SpectX turns any text-based log files into structured virtual views. SpectX query language is inspired by piping in Unix. An extensive library of built-in query functions allows analysts to compose complex queries and get advanced insights. In addition to the browser-based interface, every query can be easily executed via RESTful API, with advanced options to customize the resultset. This makes it easy to integrate SpectX with other applications in need of clean and structured data. SpectX easy-to-read pattern matching language can flexibly match any data, no need to read or write regex.Starting Price: $79/month -
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VeloDB
VeloDB
Powered by Apache Doris, VeloDB is a modern data warehouse for lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within seconds. Storage engine with real-time upsert、append and pre-aggregation. Unparalleled performance in both real-time data serving and interactive ad-hoc queries. Not just structured but also semi-structured data. Not just real-time analytics but also batch processing. Not just run queries against internal data but also work as a federate query engine to access external data lakes and databases. Distributed design to support linear scalability. Whether on-premise deployment or cloud service, separation or integration of storage and compute, resource usage can be flexibly and efficiently adjusted according to workload requirements. Built on and fully compatible with open source Apache Doris. Support MySQL protocol, functions, and SQL for easy integration with other data tools. -
41
Azure Data Lake
Microsoft
Azure Data Lake includes all the capabilities required to make it easy for developers, data scientists, and analysts to store data of any size, shape, and speed, and do all types of processing and analytics across platforms and languages. It removes the complexities of ingesting and storing all of your data while making it faster to get up and running with batch, streaming, and interactive analytics. Azure Data Lake works with existing IT investments for identity, management, and security for simplified data management and governance. It also integrates seamlessly with operational stores and data warehouses so you can extend current data applications. We’ve drawn on the experience of working with enterprise customers and running some of the largest scale processing and analytics in the world for Microsoft businesses like Office 365, Xbox Live, Azure, Windows, Bing, and Skype. Azure Data Lake solves many of the productivity and scalability challenges that prevent you from maximizing the -
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Nirveda Cognition
Nirveda Cognition
Make Smarter, Faster & More Informed Decisions. Enterprise Document Intelligence Platform to turn data into Actionable Insights. Our versatile platform uses cognitive Machine Learning and Natural Language Processing algorithms to automatically classify, extract, enrich, and integrate relevant, timely, and accurate information from your documents. The solution is delivered as a service to lower the cost of ownership and accelerate time to value. How It Works. CLASSIFY. Ingest structured, semi-structured, or unstructured documents. Identify and classify documents based on semantic understanding of language and visual cues. Extract. Extracts words, short phrases, and sections of text from printed, handwritten, and tabular data. Detects the presence of a signature or page annotation. Easily review and make corrections to the extracted data. AI uses human corrections to learn and improve. Enrich. Customizable data verification, validation, standardization and normalization. -
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Openbridge
Openbridge
Uncover insights to supercharge sales growth using code-free, fully-automated data pipelines to data lakes or cloud warehouses. A flexible, standards-based platform to unify sales and marketing data for automating insights and smarter growth. Say goodbye to messy, expensive manual data downloads. Always know what you’ll pay and only pay for what you use. Fuel your tools with quick access to analytics-ready data. As certified developers, we only work with secure, official APIs. Get started quickly with data pipelines from popular sources. Pre-built, pre-transformed, and ready-to-go data pipelines. Unlock data from Amazon Vendor Central, Amazon Seller Central, Instagram Stories, Facebook, Amazon Advertising, Google Ads, and many others. Code-free data ingestion and transformation processes allow teams to realize value from their data quickly and cost-effectively. Data is always securely stored directly in a trusted, customer-owned data destination like Databricks, Amazon Redshift, etc.Starting Price: $149 per month -
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Restructured
Kolena
Restructured is an AI-powered platform designed to help businesses extract insights from unstructured data at scale. Whether dealing with documents, images, audio, or video, it combines LLM capabilities with advanced search and retrieval methods to not only index information but also understand it in context. Restructured transforms massive datasets into actionable insights, making complex data easy to navigate and analyze.Starting Price: $99/user/month -
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GTB Technologies DLP
GTB Technologies
Data Loss Prevention is defined as a system that performs real-time data classification on data at rest and in motion while automatically enforcing data security policies. Data in motion is data going to the cloud, internet, devices, or the printer. Our solution is the technology leader. Protecting on-premises, off-premises, and the cloud whether it be Mac, Linux, or Windows; our Data Loss Prevention security engine accurately detects structured & unstructured data at the binary level. GTB is the only Data Loss Prevention solution that accurately protects data when off the network. Discover, identify, classify, inventory, index, redact, re-mediate, index, control and protect your data including PII, PCI, PHI, IP, unstructured data, structured data, FERC, NERC, SOX, GLBA & more. Our patented and patent-pending, proprietary technology is able to prevent the syncing of sensitive data to unsanctioned or private clouds, while allowing its users to automatically identify “sync folders”. -
46
Vega
Vega
Vega is an AI-native, federated security analytics platform built to give security operations teams unified visibility, detection, investigation, and response across all of their security data without requiring costly data migration or centralized ingestion. Its Security Analytics Mesh (SAM) lets analysts instantly access and query data wherever it lives, including SIEMs, data lakes, cloud services, and cold storage, using natural language or query languages, eliminating blind spots and reducing cost and maintenance overhead while expanding coverage. It delivers AI-powered detections, automated triage, and cross-environment alert correlation, translating and normalizing data from disparate sources so teams can build, deploy, and refine detection rules once and run them everywhere. Vega also continuously tunes alerts to reduce noise, uncovers hidden security gaps, and integrates with existing security stacks through pre-built connectors. -
47
Informatica Data Engineering Streaming
Informatica
AI-powered Informatica Data Engineering Streaming enables data engineers to ingest, process, and analyze real-time streaming data for actionable insights. Advanced serverless deployment option with integrated metering dashboard cuts admin overhead. Rapidly build intelligent data pipelines with CLAIRE®-powered automation, including automatic change data capture (CDC). Ingest thousands of databases and millions of files, and streaming events. Efficiently ingest databases, files, and streaming data for real-time data replication and streaming analytics. Find and inventory all data assets throughout your organization. Intelligently discover and prepare trusted data for advanced analytics and AI/ML projects. -
48
ancoraDocs
ancora Software
ancoraDocs Enterprise is a next-generation, universal document capture and forms processing system developed by ancora Software. Available both on-premise and in the cloud, it utilizes advanced "Document Understanding" technology to automatically distinguish among thousands of document types and formats. This enables high-speed capture, classification, indexing, recognition, data entry, and validation of virtually any document received by a company. The system is browser-based, facilitating easy cloud deployments, and employs machine learning techniques to eliminate complex setup processes. Additional features include robust security measures, comprehensive reporting tools, barcode recognition, and flexible import options from various sources such as email, fax, FTP, or direct scanning. -
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Logflare
Logflare
Never get surprised by a logging bill again, collect for years, query in seconds. Costs escalates quickly with typical log management solutions. To setup long term analytics on events you need to archive to a CSV and setup another data pipeline to ingest events into a custom tailored data warehouse. With Logflare and BigQuery there is no setup for long term analytics. You can ingest immediately, query in seconds and store data for years. Use our Cloudflare app and catch every request to your web service no matter what. Our Cloudflare App worker doesn't modify your request, it simply pulls the request/response data and logs to Logflare asynchronously after passing your request through. Want to monitor your Elixir app? Our library adds minimal overhead. We batch logs and use BERT binary serialization to keep payload size and serialization load low. When you sign in with your Google account, we give you access to your underlying BigQuery table.Starting Price: $5 per month -
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SAP IQ
SAP
Enhance in-the-moment decision-making with SAP IQ, our columnar relational database management system (RDBMS) optimized for Big Data analytics. Gain maximum speed, power, and security, while supporting extreme-scale enterprise data warehousing and Big Data analytics, with this affordable, efficient relational database management system (RDBMS) for SAP Business Technology Platform. Deploy as a fully managed cloud service on a major hyper scale platform. Ingest, store, and query large data volumes within a relational data lake that provides a native object storage for most file types. Provide a compatible, fully managed cloud option for SAP IQ customers that extend existing Sybase investments. Simplify the migration of existing SAP IQ databases to the cloud. Make Big Data available faster to applications and people for in-the-moment decisions.
