Alternatives to e6data
Compare e6data alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to e6data in 2026. Compare features, ratings, user reviews, pricing, and more from e6data competitors and alternatives in order to make an informed decision for your business.
-
1
Teradata VantageCloud
Teradata
Teradata VantageCloud: The complete cloud analytics and data platform for AI. Teradata VantageCloud is an enterprise-grade, cloud-native data and analytics platform that unifies data management, advanced analytics, and AI/ML capabilities in a single environment. Designed for scalability and flexibility, VantageCloud supports multi-cloud and hybrid deployments, enabling organizations to manage structured and semi-structured data across AWS, Azure, Google Cloud, and on-premises systems. It offers full ANSI SQL support, integrates with open-source tools like Python and R, and provides built-in governance for secure, trusted AI. VantageCloud empowers users to run complex queries, build data pipelines, and operationalize machine learning models—all while maintaining interoperability with modern data ecosystems. -
2
AnalyticsCreator
AnalyticsCreator
AnalyticsCreator is a metadata-driven data warehouse automation application for teams working in the Microsoft data ecosystem. It enables data engineers to design, generate, and maintain production-ready data products across Microsoft SQL Server, Azure Data Factory, and Microsoft Fabric. By using centralized metadata, AnalyticsCreator generates ELT pipelines, dimensional models, historization logic, and analytical models in a consistent, version-controlled way. This reduces manual implementation effort and tool sprawl while ensuring transparency through built-in lineage tracking and clear visibility into data dependencies and change impact. With CI/CD integration via Azure DevOps and GitHub, plus support for custom SQL, AnalyticsCreator helps data teams scale delivery, enforce standards, and maintain control as complexity grows. -
3
Snowflake
Snowflake
Snowflake is a comprehensive AI Data Cloud platform designed to eliminate data silos and simplify data architectures, enabling organizations to get more value from their data. The platform offers interoperable storage that provides near-infinite scale and access to diverse data sources, both inside and outside Snowflake. Its elastic compute engine delivers high performance for any number of users, workloads, and data volumes with seamless scalability. Snowflake’s Cortex AI accelerates enterprise AI by providing secure access to leading large language models (LLMs) and data chat services. The platform’s cloud services automate complex resource management, ensuring reliability and cost efficiency. Trusted by over 11,000 global customers across industries, Snowflake helps businesses collaborate on data, build data applications, and maintain a competitive edge.Starting Price: $2 compute/month -
4
CelerData Cloud
CelerData
CelerData is a high-performance SQL engine built to power analytics directly on data lakehouses, eliminating the need for traditional data‐warehouse ingestion pipelines. It delivers sub-second query performance at scale, supports on-the‐fly JOINs without costly denormalization, and simplifies architecture by allowing users to run demanding workloads on open format tables. Built on the open source engine StarRocks, the platform outperforms legacy query engines like Trino, ClickHouse, and Apache Druid in latency, concurrency, and cost-efficiency. With a cloud-managed service that runs in your own VPC, you retain infrastructure control and data ownership while CelerData handles maintenance and optimization. The platform is positioned to power real-time OLAP, business intelligence, and customer-facing analytics use cases and is trusted by enterprise customers (including names such as Pinterest, Coinbase, and Fanatics) who have achieved significant latency reductions and cost savings. -
5
IBM watsonx.data
IBM
Put your data to work, wherever it resides, with the open, hybrid data lakehouse for AI and analytics. Connect your data from anywhere, in any format, and access through a single point of entry with a shared metadata layer. Optimize workloads for price and performance by pairing the right workloads with the right query engine. Embed natural-language semantic search without the need for SQL, so you can unlock generative AI insights faster. Manage and prepare trusted data to improve the relevance and precision of your AI applications. Use all your data, everywhere. With the speed of a data warehouse, the flexibility of a data lake, and special features to support AI, watsonx.data can help you scale AI and analytics across your business. Choose the right engines for your workloads. Flexibly manage cost, performance, and capability with access to multiple open engines including Presto, Presto C++, Spark Milvus, and more. -
6
Databricks Data Intelligence Platform
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
7
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. -
8
A data lakehouse is a modern, open architecture that enables you to store, understand, and analyze all your data. It combines the power and richness of data warehouses with the breadth and flexibility of the most popular open source data technologies you use today. A data lakehouse can be built from the ground up on Oracle Cloud Infrastructure (OCI) to work with the latest AI frameworks and prebuilt AI services like Oracle’s language service. Data Flow is a serverless Spark service that enables our customers to focus on their Spark workloads with zero infrastructure concepts. Oracle customers want to build advanced, machine learning-based analytics over their Oracle SaaS data, or any SaaS data. Our easy- to-use data integration connectors for Oracle SaaS, make creating a lakehouse to analyze all data with your SaaS data easy and reduces time to solution.
-
9
BigLake
Google
BigLake is a storage engine that unifies data warehouses and lakes by enabling BigQuery and open-source frameworks like Spark to access data with fine-grained access control. BigLake provides accelerated query performance across multi-cloud storage and open formats such as Apache Iceberg. Store a single copy of data with uniform features across data warehouses & lakes. Fine-grained access control and multi-cloud governance over distributed data. Seamless integration with open-source analytics tools and open data formats. Unlock analytics on distributed data regardless of where and how it’s stored, while choosing the best analytics tools, open source or cloud-native over a single copy of data. Fine-grained access control across open source engines like Apache Spark, Presto, and Trino, and open formats such as Parquet. Performant queries over data lakes powered by BigQuery. Integrates with Dataplex to provide management at scale, including logical data organization.Starting Price: $5 per TB -
10
FutureAnalytica
FutureAnalytica
Ours is the world’s first & only end-to-end platform for all your AI-powered innovation needs — right from data cleansing & structuring, to creating & deploying advanced data-science models, to infusing advanced analytics algorithms with built-in Recommendation AI, to deducing the outcomes with easy-to-deduce visualization dashboards, as well as Explainable AI to backtrack how the outcomes were derived, our no-code AI platform can do it all! Our platform offers a holistic, seamless data science experience. With key features like a robust Data Lakehouse, a unique AI Studio, a comprehensive AI Marketplace, and a world-class data-science support team (on a need basis), FutureAnalytica is geared to reduce your time, efforts & costs across your data-science & AI journey. Initiate discussions with the leadership, followed by a quick technology assessment in 1–3 days. Build ready-to-integrate AI solutions using FA's fully automated data science & AI platform in 10–18 days. -
11
Archon Data Store
Platform 3 Solutions
Archon Data Store is a next-generation enterprise data archiving platform designed to help organizations manage rapid data growth, reduce legacy application costs, and meet global compliance standards. Built on a modern Lakehouse architecture, Archon Data Store unifies data lakes and data warehouses to deliver secure, scalable, and analytics-ready archival storage. The platform supports on-premise, cloud, and hybrid deployments with AES-256 encryption, audit trails, metadata governance, and role-based access control. Archon Data Store offers intelligent storage tiering, high-performance querying, and seamless integration with BI tools. It enables efficient application decommissioning, cloud migration, and digital modernization while transforming archived data into a strategic asset. With Archon Data Store, organizations can ensure long-term compliance, optimize storage costs, and unlock AI-driven insights from historical data. -
12
IOMETE
IOMETE
IOMETE is a self-hosted data lakehouse platform built on Apache Iceberg, Apache Spark, and Kubernetes. Run it on-premises or in your private cloud — your infrastructure, your data, your control. Built for enterprises in regulated industries, IOMETE eliminates third-party ICT risk at the data layer by architecture — not by contract. No SaaS dependencies. No data leaving your perimeter. Compliance with GDPR, DORA, and NIS2 is structural, not contractual. Included in one platform: - Data Lakehouse(s) - Data Catalog - SQL Editor - Apache Spark Jobs - ML Notebooks - Orchestration Engine - Spark Connect Key capabilities: Apache Iceberg-native storage, Kubernetes-native deployment (K8s + OpenShift), row/column/tag-based access control, Data Mesh support, air-gapped and zero-trust compatible. Transparent pricing — CPU-based, no per-query fees, no billing surprises.Starting Price: Free -
13
Mozart Data
Mozart Data
Mozart Data is the all-in-one modern data platform that makes it easy to consolidate, organize, and analyze data. Start making data-driven decisions by setting up a modern data stack in an hour - no engineering required. -
14
Cloudera
Cloudera
Manage and secure the data lifecycle from the Edge to AI in any cloud or data center. Operates across all major public clouds and the private cloud with a public cloud experience everywhere. Integrates data management and analytic experiences across the data lifecycle for data anywhere. Delivers security, compliance, migration, and metadata management across all environments. Open source, open integrations, extensible, & open to multiple data stores and compute architectures. Deliver easier, faster, and safer self-service analytics experiences. Provide self-service access to integrated, multi-function analytics on centrally managed and secured business data while deploying a consistent experience anywhere—on premises or in hybrid and multi-cloud. Enjoy consistent data security, governance, lineage, and control, while deploying the powerful, easy-to-use cloud analytics experiences business users require and eliminating their need for shadow IT solutions. -
15
Alibaba Cloud Data Lake Formation
Alibaba Cloud
A data lake is a centralized repository used for big data and AI computing. It allows you to store structured and unstructured data at any scale. Data Lake Formation (DLF) is a key component of the cloud-native data lake framework. DLF provides an easy way to build a cloud-native data lake. It seamlessly integrates with a variety of compute engines and allows you to manage the metadata in data lakes in a centralized manner and control enterprise-class permissions. Systematically collects structured, semi-structured, and unstructured data and supports massive data storage. Uses an architecture that separates computing from storage. You can plan resources on demand at low costs. This improves data processing efficiency to meet the rapidly changing business requirements. DLF can automatically discover and collect metadata from multiple engines and manage the metadata in a centralized manner to solve the data silo issues. -
16
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. -
17
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. -
18
DataLakeHouse.io
DataLakeHouse.io
DataLakeHouse.io (DLH.io) Data Sync provides replication and synchronization of operational systems (on-premise and cloud-based SaaS) data into destinations of their choosing, primarily Cloud Data Warehouses. Built for marketing teams and really any data team at any size organization, DLH.io enables business cases for building single source of truth data repositories, such as dimensional data warehouses, data vault 2.0, and other machine learning workloads. Use cases are technical and functional including: ELT, ETL, Data Warehouse, Pipeline, Analytics, AI & Machine Learning, Data, Marketing, Sales, Retail, FinTech, Restaurant, Manufacturing, Public Sector, and more. DataLakeHouse.io is on a mission to orchestrate data for every organization particularly those desiring to become data-driven, or those that are continuing their data driven strategy journey. DataLakeHouse.io (aka DLH.io) enables hundreds of companies to managed their cloud data warehousing and analytics solutions.Starting Price: $99 -
19
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 -
20
Narrative
Narrative
Create new streams of revenue using the data you already collect with your own branded data shop. Narrative is focused on the fundamental principles that make buying and selling data easier, safer, and more strategic. Ensure that the data you access meets your standards, whatever they may be. Know exactly who you’re working with and how the data was collected. Easily access new supply and demand for a more agile and accessible data strategy. Own your data strategy entirely with end-to-end control of inputs and outputs. Our platform simplifies and automates the most time- and labor-intensive aspects of data acquisition, so you can access new data sources in days, not months. With filters, budget controls, and automatic deduplication, you’ll only ever pay for the data you need, and nothing that you don’t.Starting Price: $0 -
21
Lyftrondata
Lyftrondata
Whether you want to build a governed delta lake, data warehouse, or simply want to migrate from your traditional database to a modern cloud data warehouse, do it all with Lyftrondata. Simply create and manage all of your data workloads on one platform by automatically building your pipeline and warehouse. Analyze it instantly with ANSI SQL, BI/ML tools, and share it without worrying about writing any custom code. Boost the productivity of your data professionals and shorten your time to value. Define, categorize, and find all data sets in one place. Share these data sets with other experts with zero codings and drive data-driven insights. This data sharing ability is perfect for companies that want to store their data once, share it with other experts, and use it multiple times, now and in the future. Define dataset, apply SQL transformations or simply migrate your SQL data processing logic to any cloud data warehouse. -
22
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. -
23
Talend Data Fabric
Qlik
Talend Data Fabric’s suite of cloud services efficiently handles all your integration and integrity challenges — on-premises or in the cloud, any source, any endpoint. Deliver trusted data at the moment you need it — for every user, every time. Ingest and integrate data, applications, files, events and APIs from any source or endpoint to any location, on-premise and in the cloud, easier and faster with an intuitive interface and no coding. Embed quality into data management and guarantee ironclad regulatory compliance with a thoroughly collaborative, pervasive and cohesive approach to data governance. Make the most informed decisions based on high quality, trustworthy data derived from batch and real-time processing and bolstered with market-leading data cleaning and enrichment tools. Get more value from your data by making it available internally and externally. Extensive self-service capabilities make building APIs easy— improve customer engagement. -
24
Sesame Software
Sesame Software
Sesame Software specializes in secure, efficient data integration and replication across diverse cloud, hybrid, and on-premise sources. Our patented scalability ensures comprehensive access to critical business data, facilitating a holistic view in the BI tools of your choice. This unified perspective empowers your own robust reporting and analytics, enabling your organization to regain control of your data with confidence. At Sesame Software, we understand what’s at stake when you need to move a massive amount of data between environments quickly—while keeping it protected, maintaining centralized access, and ensuring compliance with regulations. Over the past 30+ years, we’ve helped hundreds of organizations like Proctor & Gamble, Bank of America, and the U.S. government connect, move, store, and protect their data. -
25
Qubole
Qubole
Qubole is a simple, open, and secure Data Lake Platform for machine learning, streaming, and ad-hoc analytics. Our platform provides end-to-end services that reduce the time and effort required to run Data pipelines, Streaming Analytics, and Machine Learning workloads on any cloud. No other platform offers the openness and data workload flexibility of Qubole while lowering cloud data lake costs by over 50 percent. Qubole delivers faster access to petabytes of secure, reliable and trusted datasets of structured and unstructured data for Analytics and Machine Learning. Users conduct ETL, analytics, and AI/ML workloads efficiently in end-to-end fashion across best-of-breed open source engines, multiple formats, libraries, and languages adapted to data volume, variety, SLAs and organizational policies. -
26
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. -
27
AtScale
AtScale
AtScale helps accelerate and simplify business intelligence resulting in faster time-to-insight, better business decisions, and more ROI on your Cloud analytics investment. Eliminate repetitive data engineering tasks like curating, maintaining and delivering data for analysis. Define business definitions in one location to ensure consistent KPI reporting across BI tools. Accelerate time to insight from data while efficiently managing cloud compute costs. Leverage existing data security policies for data analytics no matter where data resides. AtScale’s Insights workbooks and models let you perform Cloud OLAP multidimensional analysis on data sets from multiple providers – with no data prep or data engineering required. We provide built-in easy to use dimensions and measures to help you quickly derive insights that you can use for business decisions. -
28
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 -
29
OpenText Analytics Database is a high-performance, scalable analytics platform that enables organizations to analyze massive data sets quickly and cost-effectively. It supports real-time analytics and in-database machine learning to deliver actionable business insights. The platform can be deployed flexibly across hybrid, multi-cloud, and on-premises environments to optimize infrastructure and reduce total cost of ownership. Its massively parallel processing (MPP) architecture handles complex queries efficiently, regardless of data size. OpenText Analytics Database also features compatibility with data lakehouse architectures, supporting formats like Parquet and ORC. With built-in machine learning and broad language support, it empowers users from SQL experts to Python developers to derive predictive insights.
-
30
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.
-
31
MaxCompute
Alibaba Cloud
MaxCompute (previously known as ODPS) is a general-purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing. MaxCompute supports various data importing solutions and distributed computing models, enabling users to effectively query massive datasets, reduce production costs, and ensure data security. Supports EB-level data storage and computing. Supports SQL, MapReduce, and Graph computational models and Message Passing Interface (MPI) iterative algorithms. Provides more efficient computing and storage services than an enterprise private cloud, and reduces the purchase cost by 20% to 30%. Provides stable offline analysis services for more than seven years, and enables multi-level sandbox protection and monitoring. MaxCompute uses tunnels to transmit data. Tunnels are scalable, and import and export PB-level data on a daily basis. You can import all data or history data through multiple tunnels. -
32
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. -
33
Hadoop
Apache Software Foundation
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures. A wide variety of companies and organizations use Hadoop for both research and production. Users are encouraged to add themselves to the Hadoop PoweredBy wiki page. Apache Hadoop 3.3.4 incorporates a number of significant enhancements over the previous major release line (hadoop-3.2). -
34
Wherobots
Wherobots
Wherobots, the Spatial Intelligence Cloud, enables any data team to analyze data about the physical world faster, at greater scale, and at lower cost compared to traditional solutions. Built by the creators of Apache Sedona, it's a compute lakehouse engine that unifies spatial and non-spatial data, automates data workflows, and runs AI on planetary scale imagery. Spatial data refers to information about places, objects, or activities. Examples include GPS points and tracks, routes, land, road, parcel, crop, and building data, as well as imagery from drones and satellites. This data is fundamental to various industries including aerospace, mobility, ag-tech, insurance, energy, telecommunications, retail, and logistics. In one solution, Wherobots handles these diverse spatial data types and formats, with customers seeing production workloads run up to 20x faster and at lower cost than popular lakehouse engines. -
35
Tweakstreet
Twineworks
Automate your Data Science. Create data automation workflows. Design on your desktop — run anywhere. A tool for modern data integration. Tweakstreet is a tool you run on your computers. It is not a service. You are always in complete control of your data. Design using a desktop app and run anywhere: your desktop, data center, or cloud servers. Connect to anything. Tweakstreet has connectors for many common data sources such as file formats, databases, and online services. We're regularly adding new connectors to new releases. File formats. Out of the box support for common data exchange formats such as: CSV, XML, and JSON files. SQL databases. You can work with popular SQL databases like Postgres, MariaDB, SQL Server, Oracle, MySQL, or DB2. In addition Tweakstreet offers generic support for any database that has JDBC drivers. Web APIs Tweakstreet supports HTTP interfaces such as REST-style APIs. First class support for OAuth 2.0 authentication enables access to popular APIs -
36
AnalyticDB
Alibaba Cloud
AnalyticDB for MySQL is a high-performance data warehousing service that is secure, stable, and easy to use. It allows you to easily create online statistical reports, multidimensional analysis solutions, and real-time data warehouses. AnalyticDB for MySQL uses a distributed computing architecture that enables it to use the elastic scaling capability of the cloud to compute tens of billions of data records in real time. AnalyticDB for MySQL stores data based on relational models and can use SQL to flexibly compute and analyze data. AnalyticDB for MySQL also allows you to easily manage databases, scale in or out nodes, and scale up or down instances. It provides various visualization and ETL tools to make enterprise data processing easier. Provides instant multidimensional analysis and can explore large amounts of data in milliseconds.Starting Price: $0.248 per hour -
37
Data Virtuality
Data Virtuality
Connect and centralize data. Transform your existing data landscape into a flexible data powerhouse. Data Virtuality is a data integration platform for instant data access, easy data centralization and data governance. Our Logical Data Warehouse solution combines data virtualization and materialization for the highest possible performance. Build your single source of data truth with a virtual layer on top of your existing data environment for high data quality, data governance, and fast time-to-market. Hosted in the cloud or on-premises. Data Virtuality has 3 modules: Pipes, Pipes Professional, and Logical Data Warehouse. Cut down your development time by up to 80%. Access any data in minutes and automate data workflows using SQL. Use Rapid BI Prototyping for significantly faster time-to-market. Ensure data quality for accurate, complete, and consistent data. Use metadata repositories to improve master data management. -
38
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. -
39
AWS Lake Formation
Amazon
AWS Lake Formation is a service that makes it easy to set up a secure data lake in days. A data lake is a centralized, curated, and secured repository that stores all your data, both in its original form and prepared for analysis. A data lake lets you break down data silos and combine different types of analytics to gain insights and guide better business decisions. Setting up and managing data lakes today involves a lot of manual, complicated, and time-consuming tasks. This work includes loading data from diverse sources, monitoring those data flows, setting up partitions, turning on encryption and managing keys, defining transformation jobs and monitoring their operation, reorganizing data into a columnar format, deduplicating redundant data, and matching linked records. Once data has been loaded into the data lake, you need to grant fine-grained access to datasets, and audit access over time across a wide range of analytics and machine learning (ML) tools and services. -
40
Azure Data Lake Storage
Microsoft
Eliminate data silos with a single storage platform. Optimize costs with tiered storage and policy management. Authenticate data using Azure Active Directory (Azure AD) and role-based access control (RBAC). And help protect data with security features like encryption at rest and advanced threat protection. Highly secure with flexible mechanisms for protection across data access, encryption, and network-level control. Single storage platform for ingestion, processing, and visualization that supports the most common analytics frameworks. Cost optimization via independent scaling of storage and compute, lifecycle policy management, and object-level tiering. Meet any capacity requirements and manage data with ease, with the Azure global infrastructure. Run large-scale analytics queries at consistently high performance. -
41
IBM Storage Scale is software-defined file and object storage that enables organizations to build a global data platform for artificial intelligence (AI), high-performance computing (HPC), advanced analytics, and other demanding workloads. Unlike traditional applications that work with structured data, today’s performance-intensive AI and analytics workloads operate on unstructured data, such as documents, audio, images, videos, and other objects. IBM Storage Scale software provides global data abstraction services that seamlessly connect multiple data sources across multiple locations, including non-IBM storage environments. It’s based on a massively parallel file system and can be deployed on multiple hardware platforms including x86, IBM Power, IBM zSystem mainframes, ARM-based POSIX client, virtual machines, and Kubernetes.Starting Price: $19.10 per terabyte
-
42
Savante
Xybion Corporation
Consolidating and validating data sets is a highly challenging and business-critical effort for many Contract Research Organizations (CROs) and drug developers who perform toxicology studies either internally or outsourced with external partners. Savante provides a mechanism for your organization to create, merge, validate, and visualize preclinical study data regardless of source or format. Savante provides a vehicle for preclinical data aggregation, analysis, and visualization in SEND format to scientific staff and management. Preclinical data from Pristima XD is automatically synchronized into the Savante repository. Data from other sources can be aggregated through migration and import, including direct loads of sent data sets. The Savante toolkit handles the necessary consolidation, study merging, control terminology mapping, and data definition file preparation. -
43
Delta Lake
Delta Lake
Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark™ and big data workloads. Data lakes typically have multiple data pipelines reading and writing data concurrently, and data engineers have to go through a tedious process to ensure data integrity, due to the lack of transactions. Delta Lake brings ACID transactions to your data lakes. It provides serializability, the strongest level of isolation level. Learn more at Diving into Delta Lake: Unpacking the Transaction Log. In big data, even the metadata itself can be "big data". Delta Lake treats metadata just like data, leveraging Spark's distributed processing power to handle all its metadata. As a result, Delta Lake can handle petabyte-scale tables with billions of partitions and files at ease. Delta Lake provides snapshots of data enabling developers to access and revert to earlier versions of data for audits, rollbacks or to reproduce experiments. -
44
Sprinkle
Sprinkle Data
Businesses today need to adapt faster with ever evolving customer requirements and preferences. Sprinkle helps you manage these expectations with agile analytics platform that meets changing needs with ease. We started Sprinkle with the goal to simplify end to end data analytics for organisations, so that they don’t worry about integrating data from various sources, changing schemas and managing pipelines. We built a platform that empowers everyone in the organisation to browse and dig deeper into the data without any technical background. Our team has worked extensively with data while building analytics systems for companies like Flipkart, Inmobi, and Yahoo. These companies succeed by maintaining dedicated teams of data scientists, business analyst and engineers churning out reports and insights. We realized that most organizations struggle for simple self-serve reporting and data exploration. So we set out to build solution that will help all companies leverage data.Starting Price: $499 per month -
45
Datametica
Datametica
At Datametica, our birds with unprecedented capabilities help eliminate business risks, cost, time, frustration, and anxiety from the entire process of data warehouse migration to the cloud. Migration of existing data warehouse, data lake, ETL, and Enterprise business intelligence to the cloud environment of your choice using Datametica automated product suite. Architecting an end-to-end migration strategy, with workload discovery, assessment, planning, and cloud optimization. Starting from discovery and assessment of your existing data warehouse to planning the migration strategy – Eagle gives clarity on what’s needed to be migrated and in what sequence, how the process can be streamlined, and what are the timelines and costs. The holistic view of the workloads and planning reduces the migration risk without impacting the business. -
46
Acho
Acho
Unify all your data in one hub with 100+ built-in and universal API data connectors. Make them accessible to your whole team. Transform data with simple points and clicks. Build robust data pipelines with built-in data manipulation tools and automated schedulers. Save hours spent on sending your data somewhere manually. Use Workflow to automate the process from databases to BI tools, from apps to databases. A full suite of data cleaning and transformation tools is available in the no-code format, eliminating the need to write complex expressions or code. Data is only useful when insights are drawn. Upgrade your database to an analytical engine with native cloud-based BI tools. No connectors are needed, all data projects on Acho can be analyzed and visualized on our Visual Panel off the shelf, at a blazing-fast speed too. -
47
Muspell HDP
314e Corporation
Muspell HDP by 314e Corporation is a cloud-native, FHIR-native modern data warehouse built specifically for healthcare operators. It uses the FHIR standard at its core to integrate disparate data types, such as patient records, claims, and lab results, into a unified and standardized format, reducing complexity and cost associated with custom models. It is scalable, capable of handling data for tens of thousands to millions of patients while delivering high performance. It includes pre-built analytics dashboards and templates for healthcare metrics (such as HEDIS, eCQM, QIP), curated reference datasets (e.g., Hospital Price Transparency, NPPES), and managed ETL services that keep data fresh, near-real time. The user interface is designed for non-engineers to build charts, dashboards, and queries easily. Features also include AI-ready infrastructure (natural language queries, predictive analytics), and built-in compliance and security, including HIPAA and HITRUST standards. -
48
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 -
49
Scalytics Connect
Scalytics
Scalytics Connect enables AI and ML to process and analyze data, makes it easier and more secure to use different data processing platforms at the same time. Built by the inventors of Apache Wayang, Scalytics Connect is the most enhanced data management platform, reducing the complexity of ETL data pipelines dramatically. Scalytics Connect is a data management and ETL platform that helps organizations unlock the power of their data, regardless of where it resides. It empowers businesses to break down data silos, simplify access, and gain valuable insights through a variety of features, including: - AI-powered ETL: Automates tasks like data extraction, transformation, and loading, freeing up your resources for more strategic work. - Unified Data Landscape: Breaks down data silos and provides a holistic view of all your data, regardless of its location or format. - Effortless Scaling: Handles growing data volumes with ease, so you never get bottlenecked by information overloadStarting Price: $0 -
50
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.
