Alternatives to Azure HDInsight
Compare Azure HDInsight alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Azure HDInsight in 2024. Compare features, ratings, user reviews, pricing, and more from Azure HDInsight competitors and alternatives in order to make an informed decision for your business.
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Google Cloud Platform
Google
Google Cloud is a cloud-based service that allows you to create anything from simple websites to complex applications for businesses of all sizes. New customers get $300 in free credits to run, test, and deploy workloads. All customers can use 25+ products for free, up to monthly usage limits. Use Google's core infrastructure, data analytics & machine learning. Secure and fully featured for all enterprises. Tap into big data to find answers faster and build better products. Grow from prototype to production to planet-scale, without having to think about capacity, reliability or performance. From virtual machines with proven price/performance advantages to a fully managed app development platform. Scalable, resilient, high performance object storage and databases for your applications. State-of-the-art software-defined networking products on Google’s private fiber network. Fully managed data warehousing, batch and stream processing, data exploration, Hadoop/Spark, and messaging. -
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StarTree
StarTree
StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. • Gain critical real-time insights to run your business • Seamlessly integrate data streaming and batch data • High performance in throughput and low-latency at petabyte scale • Fully-managed cloud service • Tiered storage to optimize cloud performance & spend • Fully-secure & enterprise-ready -
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Centralpoint
Oxcyon
Centralpoint is a Digital Experience Platform, and in Gartner's Magic Quadrant. It is used by over 350 clients worldwide going beyond Enterprise Content Management, securely authenticating (AD/SAML,OpenID, oAuth) all users for self service interaction. Centralpoint automatically aggregates your information from disparate sources, applying rich metadata against your rules, yielding true Knowledge Management; allowing you to search and relate disparate sets of data from anywhere. Centralpoint offers the most robust Module Gallery, out of the box, and can be installed on premise or in the Cloud. Be sure to see our solutions for Automating Metadata, Automating retention Policy Management, and simplifying the mash up of disparate data for the benefit of AI (Artificial Intelligence). Centralpoint is often used as an intelligent altternative to Sharepoint, allowing easy Migration tools. It can also be used for any secure portal solution for your public sites, Intranets, Members or Extranets. -
4
IRI Voracity
IRI, The CoSort Company
Voracity is the only high-performance, all-in-one data management platform accelerating AND consolidating the key activities of data discovery, integration, migration, governance, and analytics. Voracity helps you control your data in every stage of the lifecycle, and extract maximum value from it. Only in Voracity can you: 1) CLASSIFY, profile and diagram enterprise data sources 2) Speed or LEAVE legacy sort and ETL tools 3) MIGRATE data to modernize and WRANGLE data to analyze 4) FIND PII everywhere and consistently MASK it for referential integrity 5) Score re-ID risk and ANONYMIZE quasi-identifiers 6) Create and manage DB subsets or intelligently synthesize TEST data 7) Package, protect and provision BIG data 8) Validate, scrub, enrich and unify data to improve its QUALITY 9) Manage metadata and MASTER data. Use Voracity to comply with data privacy laws, de-muck and govern the data lake, improve the reliability of your analytics, and create safe, smart test data -
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MicroStrategy
MicroStrategy
Quickly deploy consumer-grade BI experiences for every role, on any device, with the platform that provides sub-second response at enterprise scale. Build consumer-grade intelligence applications, empower users with data discovery, and seamlessly push content to employees, partners, and customers in minutes. Using our open platform, inject the data you trust into the tools you love. Learn about MicroStrategy's #1-rated platform for Embedded Analytics. Deploy mobile intelligence solutions for every user on any device, customized for your organization with no coding required. The fastest, most efficient way to run your Intelligent Enterprise. -
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Striim
Striim
Data integration for your hybrid cloud. Modern, reliable data integration across your private and public cloud. All in real-time with change data capture and data streams. Built by the executive & technical team from GoldenGate Software, Striim brings decades of experience in mission-critical enterprise workloads. Striim scales out as a distributed platform in your environment or in the cloud. Scalability is fully configurable by your team. Striim is fully secure with HIPAA and GDPR compliance. Built ground up for modern enterprise workloads in the cloud or on-premise. Drag and drop to create data flows between your sources and targets. Process, enrich, and analyze your streaming data with real-time SQL queries. -
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E-MapReduce
Alibaba
EMR is an all-in-one enterprise-ready big data platform that provides cluster, job, and data management services based on open-source ecosystems, such as Hadoop, Spark, Kafka, Flink, and Storm. Alibaba Cloud Elastic MapReduce (EMR) is a big data processing solution that runs on the Alibaba Cloud platform. EMR is built on Alibaba Cloud ECS instances and is based on open-source Apache Hadoop and Apache Spark. EMR allows you to use the Hadoop and Spark ecosystem components, such as Apache Hive, Apache Kafka, Flink, Druid, and TensorFlow, to analyze and process data. You can use EMR to process data stored on different Alibaba Cloud data storage service, such as Object Storage Service (OSS), Log Service (SLS), and Relational Database Service (RDS). You can quickly create clusters without the need to configure hardware and software. All maintenance operations are completed on its Web interface. -
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Amazon EMR
Amazon
Amazon EMR is the industry-leading cloud big data platform for processing vast amounts of data using open-source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. With EMR you can run Petabyte-scale analysis at less than half of the cost of traditional on-premises solutions and over 3x faster than standard Apache Spark. For short-running jobs, you can spin up and spin down clusters and pay per second for the instances used. For long-running workloads, you can create highly available clusters that automatically scale to meet demand. If you have existing on-premises deployments of open-source tools such as Apache Spark and Apache Hive, you can also run EMR clusters on AWS Outposts. Analyze data using open-source ML frameworks such as Apache Spark MLlib, TensorFlow, and Apache MXNet. Connect to Amazon SageMaker Studio for large-scale model training, analysis, and reporting. -
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Azure Databricks
Microsoft
Unlock insights from all your data and build artificial intelligence (AI) solutions with Azure Databricks, set up your Apache Spark™ environment in minutes, autoscale, and collaborate on shared projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java, and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch, and scikit-learn. Azure Databricks provides the latest versions of Apache Spark and allows you to seamlessly integrate with open source libraries. Spin up clusters and build quickly in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. Take advantage of autoscaling and auto-termination to improve total cost of ownership (TCO). -
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Google Cloud Dataproc
Google
Dataproc makes open source data and analytics processing fast, easy, and more secure in the cloud. Build custom OSS clusters on custom machines faster. Whether you need extra memory for Presto or GPUs for Apache Spark machine learning, Dataproc can help accelerate your data and analytics processing by spinning up a purpose-built cluster in 90 seconds. Easy and affordable cluster management. With autoscaling, idle cluster deletion, per-second pricing, and more, Dataproc can help reduce the total cost of ownership of OSS so you can focus your time and resources elsewhere. Security built in by default. Encryption by default helps ensure no piece of data is unprotected. With JobsAPI and Component Gateway, you can define permissions for Cloud IAM clusters, without having to set up networking or gateway nodes. -
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Apache Spark
Apache Software Foundation
Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources. -
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IBM Db2 Big SQL
IBM
A hybrid SQL-on-Hadoop engine delivering advanced, security-rich data query across enterprise big data sources, including Hadoop, object storage and data warehouses. IBM Db2 Big SQL is an enterprise-grade, hybrid ANSI-compliant SQL-on-Hadoop engine, delivering massively parallel processing (MPP) and advanced data query. Db2 Big SQL offers a single database connection or query for disparate sources such as Hadoop HDFS and WebHDFS, RDMS, NoSQL databases, and object stores. Benefit from low latency, high performance, data security, SQL compatibility, and federation capabilities to do ad hoc and complex queries. Db2 Big SQL is now available in 2 variations. It can be integrated with Cloudera Data Platform, or accessed as a cloud-native service on the IBM Cloud Pak® for Data platform. Access and analyze data and perform queries on batch and real-time data across sources, like Hadoop, object stores and data warehouses. -
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WarpStream
WarpStream
WarpStream is an Apache Kafka-compatible data streaming platform built directly on top of object storage, with no inter-AZ networking costs, no disks to manage, and infinitely scalable, all within your VPC. WarpStream is deployed as a stateless and auto-scaling agent binary in your VPC with no local disks to manage. Agents stream data directly to and from object storage with no buffering on local disks and no data tiering. Create new “virtual clusters” in our control plane instantly. Support different environments, teams, or projects without managing any dedicated infrastructure. WarpStream is protocol compatible with Apache Kafka, so you can keep using all your favorite tools and software. No need to rewrite your application or use a proprietary SDK. Just change the URL in your favorite Kafka client library and start streaming. Never again have to choose between reliability and your budget.Starting Price: $2,987 per month -
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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. -
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Arcadia Data
Arcadia Data
Arcadia Data provides the first visual analytics and BI platform native to Hadoop and cloud (big data) that delivers the scale, performance, and agility business users need for both real-time and historical insights. Its flagship product, Arcadia Enterprise, was built from inception for big data platforms such as Apache Hadoop, Apache Spark, Apache Kafka, and Apache Solr, in the cloud and/or on-premises. Using artificial intelligence (AI) and machine learning (ML), Arcadia Enterprise streamlines the self-service analytics process with search-based BI and visualization recommendations. It enables real-time, high-definition insights in use cases like data lakes, cybersecurity, connected IoT devices, and customer intelligence. Arcadia Enterprise is deployed by some of the world’s leading brands, including Procter & Gamble, Citibank, Nokia, Royal Bank of Canada, Kaiser Permanente, HPE, and Neustar. -
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doolytic
doolytic
doolytic is leading the way in big data discovery, the convergence of data discovery, advanced analytics, and big data. doolytic is rallying expert BI users to the revolution in self-service exploration of big data, revealing the data scientist in all of us. doolytic is an enterprise software solution for native discovery on big data. doolytic is based on best-of-breed, scalable, open-source technologies. Lightening performance on billions of records and petabytes of data. Structured, unstructured and real-time data from any source. Sophisticated advanced query capabilities for expert users, Integration with R for advanced and predictive applications. Search, analyze, and visualize data from any format, any source in real-time with the flexibility of Elastic. Leverage the power of Hadoop data lakes with no latency and concurrency issues. doolytic solves common BI problems and enables big data discovery without clumsy and inefficient workarounds. -
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GeoSpock
GeoSpock
GeoSpock enables data fusion for the connected world with GeoSpock DB – the space-time analytics database. GeoSpock DB is a unique, cloud-native database optimised for querying for real-world use cases, able to fuse multiple sources of Internet of Things (IoT) data together to unlock its full value, whilst simultaneously reducing complexity and cost. GeoSpock DB enables efficient storage, data fusion, and rapid programmatic access to data, and allows you to run ANSI SQL queries and connect to analytics tools via JDBC/ODBC connectors. Users are able to perform analysis and share insights using familiar toolsets, with support for common BI tools (such as Tableau™, Amazon QuickSight™, and Microsoft Power BI™), and Data Science and Machine Learning environments (including Python Notebooks and Apache Spark). The database can also be integrated with internal applications and web services – with compatibility for open-source and visualisation libraries such as Kepler and Cesium.js. -
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Hopsworks
Logical Clocks
Hopsworks is an open-source Enterprise platform for the development and operation of Machine Learning (ML) pipelines at scale, based around the industry’s first Feature Store for ML. You can easily progress from data exploration and model development in Python using Jupyter notebooks and conda to running production quality end-to-end ML pipelines, without having to learn how to manage a Kubernetes cluster. Hopsworks can ingest data from the datasources you use. Whether they are in the cloud, on‑premise, IoT networks, or from your Industry 4.0-solution. Deploy on‑premises on your own hardware or at your preferred cloud provider. Hopsworks will provide the same user experience in the cloud or in the most secure of air‑gapped deployments. Learn how to set up customized alerts in Hopsworks for different events that are triggered as part of the ingestion pipeline.Starting Price: $1 per month -
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jethro
jethro
Data-driven decision-making has unleashed a surge of business data and a rise in user demand to analyze it. This trend drives IT departments to migrate off expensive Enterprise Data Warehouses (EDW) toward cost-effective Big Data platforms like Hadoop or AWS. These new platforms come with a Total Cost of Ownership (TCO) that is about 10 times lower. They are not ideal for interactive BI applications, however, as they fail to match the high performance and user concurrency of legacy EDWs. For this exact reason, we developed Jethro. Customers use Jethro for interactive BI on Big Data. Jethro is a transparent middle tier that requires no changes to existing apps or data. It is self-driving with no maintenance required. Jethro is compatible with BI tools like Tableau, Qlik, and Microstrategy and is data source agnostic. Jethro delivers on the demands of business users allowing for thousands of concurrent users to run complicated queries over billions of records. -
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Apache Druid
Druid
Apache Druid is an open source distributed data store. Druid’s core design combines ideas from data warehouses, timeseries databases, and search systems to create a high performance real-time analytics database for a broad range of use cases. Druid merges key characteristics of each of the 3 systems into its ingestion layer, storage format, querying layer, and core architecture. Druid stores and compresses each column individually, and only needs to read the ones needed for a particular query, which supports fast scans, rankings, and groupBys. Druid creates inverted indexes for string values for fast search and filter. Out-of-the-box connectors for Apache Kafka, HDFS, AWS S3, stream processors, and more. Druid intelligently partitions data based on time and time-based queries are significantly faster than traditional databases. Scale up or down by just adding or removing servers, and Druid automatically rebalances. Fault-tolerant architecture routes around server failures. -
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Starburst Enterprise
Starburst Data
Starburst helps you make better decisions with fast access to all your data; Without the complexity of data movement and copies. Your company has more data than ever before, but your data teams are stuck waiting to analyze it. Starburst unlocks access to data where it lives, no data movement required, giving your teams fast & accurate access to more data for analysis. Starburst Enterprise is a fully supported, production-tested and enterprise-grade distribution of open source Trino (formerly Presto® SQL). It improves performance and security while making it easy to deploy, connect, and manage your Trino environment. Through connecting to any source of data – whether it’s located on-premise, in the cloud, or across a hybrid cloud environment – Starburst lets your team use the analytics tools they already know & love while accessing data that lives anywhere. -
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EspressReport ES
Quadbase Systems
EspressRepot ES (Enterprise Server) is a web and desktop-based software that allows users to develop stunning and interactive data visualization and reporting. The platform offers full Java EE integration, to draw data from data sources such as Bid Data (Hadoop, Spark, and MongoDB), ad-hoc queries and reports, online map support, mobile compatibility, alert monitor, and many other amazing features. -
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Apache Storm
Apache Software Foundation
Apache Storm is a free and open source distributed realtime computation system. Apache Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Apache Storm is simple, can be used with any programming language, and is a lot of fun to use! Apache Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Apache Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate. Apache Storm integrates with the queueing and database technologies you already use. An Apache Storm topology consumes streams of data and processes those streams in arbitrarily complex ways, repartitioning the streams between each stage of the computation however needed. Read more in the tutorial. -
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Oracle Cloud Infrastructure (OCI) Data Flow is a fully managed Apache Spark service to perform processing tasks on extremely large data sets without infrastructure to deploy or manage. This enables rapid application delivery because developers can focus on app development, not infrastructure management. OCI Data Flow handles infrastructure provisioning, network setup, and teardown when Spark jobs are complete. Storage and security are also managed, which means less work is required for creating and managing Spark applications for big data analysis. With OCI Data Flow, there are no clusters to install, patch, or upgrade, which saves time and operational costs for projects. OCI Data Flow runs each Spark job in private dedicated resources, eliminating the need for upfront capacity planning. With OCI Data Flow, IT only needs to pay for the infrastructure resources that Spark jobs use while they are running.Starting Price: $0.0085 per GB per hour
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DoubleCloud
DoubleCloud
Save time & costs by streamlining data pipelines with zero-maintenance open source solutions. From ingestion to visualization, all are integrated, fully managed, and highly reliable, so your engineers will love working with data. You choose whether to use any of DoubleCloud’s managed open source services or leverage the full power of the platform, including data storage, orchestration, ELT, and real-time visualization. We provide leading open source services like ClickHouse, Kafka, and Airflow, with deployment on Amazon Web Services or Google Cloud. Our no-code ELT tool allows real-time data syncing between systems, fast, serverless, and seamlessly integrated with your existing infrastructure. With our managed open-source data visualization you can simply visualize your data in real time by building charts and dashboards. We’ve designed our platform to make the day-to-day life of engineers more convenient.Starting Price: $0.024 per 1 GB per month -
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OctoData
SoyHuCe
OctoData is deployed at a lower cost, in Cloud hosting and includes personalized support from the definition of your needs to the use of the solution. OctoData is based on innovative open-source technologies and knows how to adapt to open up to future possibilities. Its Supervisor offers a management interface that allows you to quickly capture, store and exploit a growing quantity and variety of data. With OctoData, prototype and industrialize your massive data recovery solutions in the same environment, including in real time. Thanks to the exploitation of your data, obtain precise reports, explore new possibilities, increase your productivity and gain in profitability. -
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Azure Data Lake Analytics
Microsoft
Easily develop and run massively parallel data transformation and processing programs in U-SQL, R, Python, and .NET over petabytes of data. With no infrastructure to manage, you can process data on demand, scale instantly, and only pay per job. Process big data jobs in seconds with Azure Data Lake Analytics. There is no infrastructure to worry about because there are no servers, virtual machines, or clusters to wait for, manage, or tune. Instantly scale the processing power, measured in Azure Data Lake Analytics Units (AU), from one to thousands for each job. You only pay for the processing that you use per job. Act on all of your data with optimized data virtualization of your relational sources such as Azure SQL Database and Azure Synapse Analytics. Your queries are automatically optimized by moving processing close to the source data without data movement, which maximizes performance and minimizes latency.Starting Price: $2 per hour -
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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). -
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QuerySurge
RTTS
QuerySurge leverages AI to automate the data validation and ETL testing of Big Data, Data Warehouses, Business Intelligence Reports and Enterprise Apps/ERPs with full DevOps functionality for continuous testing. Use Cases - Data Warehouse & ETL Testing - Hadoop & NoSQL Testing - DevOps for Data / Continuous Testing - Data Migration Testing - BI Report Testing - Enterprise App/ERP Testing QuerySurge Features - Projects: Multi-project support - AI: automatically create datas validation tests based on data mappings - Smart Query Wizards: Create tests visually, without writing SQL - Data Quality at Speed: Automate the launch, execution, comparison & see results quickly - Test across 200+ platforms: Data Warehouses, Hadoop & NoSQL lakes, databases, flat files, XML, JSON, BI Reports - DevOps for Data & Continuous Testing: RESTful API with 60+ calls & integration with all mainstream solutions - Data Analytics & Data Intelligence: Analytics dashboard & reports -
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Keen
Keen.io
Keen is the fully managed event streaming platform. Built upon trusted Apache Kafka, we make it easier than ever for you to collect massive volumes of event data with our real-time data pipeline. Use Keen’s powerful REST API and SDKs to collect event data from anything connected to the internet. Our platform allows you to store your data securely decreasing your operational and delivery risk with Keen. With storage infrastructure powered by Apache Cassandra, data is totally secure through transfer through HTTPS and TLS, then stored with multi-layer AES encryption. Once data is securely stored, utilize our Access Keys to be able to present data in arbitrary ways without having to re-architect your security or data model. Or, take advantage of Role-based Access Control (RBAC), allowing for completely customizable permission tiers, down to specific data points or queries.Starting Price: $149 per month -
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Tencent Cloud Elastic MapReduce
Tencent
EMR enables you to scale the managed Hadoop clusters manually or automatically according to your business curves or monitoring metrics. EMR's storage-computation separation even allows you to terminate a cluster to maximize resource efficiency. EMR supports hot failover for CBS-based nodes. It features a primary/secondary disaster recovery mechanism where the secondary node starts within seconds when the primary node fails, ensuring the high availability of big data services. The metadata of its components such as Hive supports remote disaster recovery. Computation-storage separation ensures high data persistence for COS data storage. EMR is equipped with a comprehensive monitoring system that helps you quickly identify and locate cluster exceptions to ensure stable cluster operations. VPCs provide a convenient network isolation method that facilitates your network policy planning for managed Hadoop clusters. -
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SigView
Sigmoid
Get access to granular data for effortless slice & dice on billions of rows, and ensure real-time reporting in seconds! Sigview is a plug-n-play real-time data analytics tool by Sigmoid to carry exploratory data analysis. Custom built on Apache Spark, Sigview is capable of drilling down into massive data sets within a few seconds. Used by around 30k users across the globe to analyze billions of ad impressions, Sigview is designed to give real-time access to your Programmatic and non-programmatic data by analyzing enormous data sets while creating real-time reports. Whether it is optimizing your ad campaigns or discovering new inventory or generating revenue opportunities with changing times, Sigview is your go-to platform for all your reporting needs. Connects to multiple data sources like DFP, Pixel Servers, Audience and viewability partners to ingest data in any format and location maintaining data latency of less than 15 minutes. -
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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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Kyligence
Kyligence
Let Kyligence Zen take care of collecting, organizing, and analyzing your metrics so you can focus more on taking action Kyligence Zen is the go-to low-code metrics platform to define, collect, and analyze your business metrics. It empowers users to quickly connect their data sources, define their business metrics, uncover hidden insights in minutes, and share them across their organization. Kyligence Enterprise provides diverse solutions based on on-premise, public cloud, and private cloud, helping enterprises of any size to simplify multidimensional analysis based on massive amounts of data according to their business needs. Kyligence Enterprise, based on Apache Kylin, provides sub-second standard SQL query responses based on PB-scale datasets, simplifying multidimensional data analysis on data lakes for enterprises and enabling business users to quickly discover business value in massive amounts of data and drive better business decisions. -
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ProjectPro
ProjectPro.io
ProjectPro is the world's only ready-made, end-to-end projects platform. We provide ready-made AI/ML/Big Data/Cloud project templates to solve real-world business problems. Developers can get their work done faster and upskill by getting exposure to real-world use cases. ProjectPro offers Solved End-to-End, Ready to Deploy, Enterprise-Grade Big Data, and Data Science Projects for Reuse and Upskilling. Each project solves a real business problem end-to-end and comes with solution code, explanation videos, cloud lab, and tech support. Stop going to multiple online forums to search for solutions. Get ready-made project solutions from data extraction to analysis to visualization to deployment Our investors include Sequoia Capital (the first investor in Apple, Google, YouTube etc) and YCombinator (investors in Stripe, Dropbox, Airbnb etc). Why Project Pro - End-to-end implementation - Real industry grade projects by industry experts - Ready-made solutionsStarting Price: $1400 USD -
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One platform, four solutions. INDICA connects to all company applications and data sources. It indexes all live data and gives you grip on your complete data landscape. With its platform as a basis, INDICA offers four solutions. INDICA Enterprise Search enables access to all the corporate data sources through one interface. It indexes all structured and unstructured data and ranks the results to relevance. INDICA eDiscovery can be set up as a case by case platform and as a platform that will allow you to run fraud or compliance investigations on the fly. The INDICA Privacy Suite provides you with an extensive toolkit to allow your organization to comply to GDPR and CCPA laws and to remain compliant. INDICA Data Lifecycle Management allows you to take control of your corporate data, keep track of your data and clean or migrate your data. INDICA’s data platform consists of a broad set of features to get in control of your data.
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The Autonomous Data Engine
Infoworks
There is a consistent “buzz” today about how leading companies are harnessing big data for competitive advantage. Your organization is striving to become one of those market-leading companies. However, the reality is that over 80% of big data projects fail to deploy to production because project implementation is a complex, resource-intensive effort that takes months or even years. The technology is complicated, and the people who have the necessary skills are either extremely expensive or impossible to find. Automates the complete data workflow from source to consumption. Automates migration of data and workloads from legacy Data Warehouse systems to big data platforms. Automates orchestration and management of complex data pipelines in production. Alternative approaches such as stitching together multiple point solutions or custom development are expensive, inflexible, time-consuming and require specialized skills to assemble and maintain. -
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Instaclustr
Instaclustr
Instaclustr is the Open Source-as-a-Service company, delivering reliability at scale. We operate an automated, proven, and trusted managed environment, providing database, analytics, search, and messaging. We enable companies to focus internal development and operational resources on building cutting edge customer-facing applications. Instaclustr works with cloud providers including AWS, Heroku, Azure, IBM Cloud, and Google Cloud Platform. The company has SOC 2 certification and provides 24/7 customer support.Starting Price: $20 per node per month -
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Privacera
Privacera
At the intersection of data governance, privacy, and security, Privacera’s unified data access governance platform maximizes the value of data by providing secure data access control and governance across hybrid- and multi-cloud environments. The hybrid platform centralizes access and natively enforces policies across multiple cloud services—AWS, Azure, Google Cloud, Databricks, Snowflake, Starburst and more—to democratize trusted data enterprise-wide without compromising compliance with regulations such as GDPR, CCPA, LGPD, or HIPAA. Trusted by Fortune 500 customers across finance, insurance, retail, healthcare, media, public and the federal sector, Privacera is the industry’s leading data access governance platform that delivers unmatched scalability, elasticity, and performance. Headquartered in Fremont, California, Privacera was founded in 2016 to manage cloud data privacy and security by the creators of Apache Ranger™ and Apache Atlas™. -
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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. -
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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. -
42
Apache Arrow
The Apache Software Foundation
Apache Arrow defines a language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware like CPUs and GPUs. The Arrow memory format also supports zero-copy reads for lightning-fast data access without serialization overhead. Arrow's libraries implement the format and provide building blocks for a range of use cases, including high performance analytics. Many popular projects use Arrow to ship columnar data efficiently or as the basis for analytic engines. Apache Arrow is software created by and for the developer community. We are dedicated to open, kind communication and consensus decisionmaking. Our committers come from a range of organizations and backgrounds, and we welcome all to participate with us. -
43
Azure Data Share
Microsoft
Share data, in any format and any size, from multiple sources with other organizations. Easily control what you share, who receives your data, and the terms of use. Data Share provides full visibility into your data-sharing relationships with a user-friendly interface. Share data in just a few clicks, or build your own application using the REST API. Serverless code-free data-sharing service that requires no infrastructure setup or management. Intuitive interface to govern all your data-sharing relationships. Automated data-sharing processes for productivity and predictability. Secure data-sharing service that uses underlying Azure security measures. Share structured and unstructured data from multiple Azure data stores with other organizations in just a few clicks. There’s no infrastructure to set up or manage, no SAS keys are required, and sharing is all code-free. You control data access and set terms of use aligned with your enterprise policies.Starting Price: $0.05 per dataset-snapshot -
44
Oracle Big Data Service
Oracle
Oracle Big Data Service makes it easy for customers to deploy Hadoop clusters of all sizes, with VM shapes ranging from 1 OCPU to a dedicated bare metal environment. Customers choose between high-performance NVmE storage or cost-effective block storage, and can grow or shrink their clusters. Quickly create Hadoop-based data lakes to extend or complement customer data warehouses, and ensure that all data is both accessible and managed cost-effectively. Query, visualize and transform data so data scientists can build machine learning models using the included notebook with its R, Python and SQL support. Move customer-managed Hadoop clusters to a fully-managed cloud-based service, reducing management costs and improving resource utilization.Starting Price: $0.1344 per hour -
45
Isima
Isima
bi(OS)® delivers unparalleled speed to insight for data app builders in a unified manner. With bi(OS)®, the complete life-cycle of building data apps takes hours to days. This includes adding varied data sources, deriving real-time insights, and deploying to production. Join enterprise data teams across industries and become the data superhero your business deserves. The trifecta of Open Source, Cloud, and SaaS has failed to deliver the promised data-driven impact. All of the enterprises' investments have been in data movement and integration, which isn't sustainable. There is a dire need for a new approach to data, built with enterprise empathy in mind. bi(OS)® is built by reimagining first principles in enterprise data management, from ingest to insight. It serves API, AI, and BI builders in a unified manner, to achieve data-driven impact in days. Engineers build enduring moat as a symphony emerges between IT teams, tools, and processes. -
46
Robin.io
Robin.io
ROBIN is the industry’s first hyper-converged Kubernetes platform for big data, databases, and AI/ML. The platform provides a self-service App-store experience for the deployment of any application, anywhere – runs on-premises in your private data center or in public-cloud (AWS, Azure, GCP) environments. Hyper-converged Kubernetes is a software-defined application orchestration framework that combines containerized storage, networking, compute (Kubernetes), and the application management layer into a single system. Our approach extends Kubernetes for data-intensive applications such as Hortonworks, Cloudera, Elastic stack, RDBMS, NoSQL databases, and AI/ML apps. Facilitates simpler and faster roll-out of critical Enterprise IT and LoB initiatives, such as containerization, cloud-migration, cost-consolidation, and productivity improvement. Solves the fundamental challenges of running big data and databases in Kubernetes. -
47
PHEMI Health DataLab
PHEMI Systems
The PHEMI Trustworthy Health DataLab is a unique, cloud-based, integrated big data management system that allows healthcare organizations to enhance innovation and generate value from healthcare data by simplifying the ingestion and de-identification of data with NSA/military-grade governance, privacy, and security built-in. Conventional products simply lock down data, PHEMI goes further, solving privacy and security challenges and addressing the urgent need to secure, govern, curate, and control access to privacy-sensitive personal healthcare information (PHI). This improves data sharing and collaboration inside and outside of an enterprise—without compromising the privacy of sensitive information or increasing administrative burden. PHEMI Trustworthy Health DataLab can scale to any size of organization, is easy to deploy and manage, connects to hundreds of data sources, and integrates with popular data science and business analysis tools. -
48
Sisense
Sisense
Embed analytics into any application or workflow to make critical decisions – with confidence. Infuse analytics into everyday applications and workflows to drive better, faster decisions, for your business and your customers. Integrate customized analytics into your applications and products to make analytics intuitive and user-friendly. Boost product engagement, adoption, and retention with the AI-driven predictive analytics platform built for business success. Prepare, analyze, and explore data from multiple sources with Sisense, a leading Business Intelligence (BI) reporting software. Trusted by industry-leading companies, such as NASDAQ, Phillips, and Airbus, Sisense offers an end-to-end, agile BI platform that helps business make smarter, faster data-driven decisions. Sisense features an open, single-stack architecture, best-in-class analytics engine, machine learning, and delivery of insights beyond the dashboard. -
49
IBM Analytics Engine provides an architecture for Hadoop clusters that decouples the compute and storage tiers. Instead of a permanent cluster formed of dual-purpose nodes, the Analytics Engine allows users to store data in an object storage layer such as IBM Cloud Object Storage and spins up clusters of computing notes when needed. Separating compute from storage helps to transform the flexibility, scalability and maintainability of big data analytics platforms. Build on an ODPi compliant stack with pioneering data science tools with the broader Apache Hadoop and Apache Spark ecosystem. Define clusters based on your application's requirements. Choose the appropriate software pack, version, and size of the cluster. Use as long as required and delete as soon as an application finishes jobs. Configure clusters with third-party analytics libraries and packages. Deploy workloads from IBM Cloud services like machine learning.Starting Price: $0.014 per hour
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50
IBM Granite
IBM
IBM® Granite™ is a family of artificial intelligence (AI) models purpose-built for business, engineered from scratch to help ensure trust and scalability in AI-driven applications. Open source Granite models are available today. We make AI as accessible as possible for as many developers as possible. That’s why we have open-sourced core Granite Code, Time Series, Language, and GeoSpatial models and made them available on Hugging Face under permissive Apache 2.0 license that enables broad, unencumbered commercial usage. All Granite models are trained on carefully curated data, with industry-leading levels of transparency about the data that went into them. We have also open-sourced the tools we use to ensure the data is high quality and up to the standards that enterprise-grade applications demand.Starting Price: Free
