Exasol
by ExasolExasol suits organizations needing multi-departmental analytics, in-database machine learning or AI, or complex data integration and virtualization.
Facts read 23 Sep 2026 – 15 Oct 2026
Big data analytics software helps you compare tools for working with large data workloads. Use this list to review pricing, deployment, processing, scale, connectors, visualization and query-language details.
| Name | In a line | Record score | Price from | Try it free | Runs on | Facts read |
|---|---|---|---|---|---|---|
| 01 Exasol | Exasol suits organizations needing multi-departmental analytics, in-database machine learning or AI, or complex data integration and virtualization. | 6.0 | $3.30 a month | Free plan | Web, Windows, Mac, Linux | 14 Oct 2026 |
| 02 SingleStore Helios | Helios suits teams that need a cloud database for transactional and analytical work, with multiple data models or AI workloads. | 6.0 | Free plan | Free plan | Web, Windows, Mac, Linux | 15 Oct 2026 |
| 03 Apache Beam | Apache Beam suits data and software developers building batch or streaming pipelines for supported execution back ends. | 5.6 | Free plan | Free plan | Web, Windows, Mac, Linux | 14 Oct 2026 |
| 04 Starburst Galaxy | Starburst recommends Galaxy for organizations that do not yet have resources to manage complex data clusters. | 5.6 | Free plan | Free plan | Web, Linux, API | 30 Sep 2026 |
| 05 Teradata VantageCloud | 5.6 | Free plan | Free plan | Web, Linux, API, Self-hosted | 2 Oct 2026 | |
| 06 ClickHouse Cloud | 5.5 | $25.30 a month | Free trial | Web, Windows, Mac, Linux | 15 Oct 2026 | |
| 07 Starburst Enterprise Context Layer | It is aimed at teams that need governed data products and controlled access across analytics and AI use. | 5.5 | $0.50 usage-based | Free plan | Web, API, Self-hosted | 15 Oct 2026 |
| 08 PrestoDB | PrestoDB is for users who need to run distributed SQL queries across heterogeneous data sources and can manage a self-hosted deployment. | 5.4 | Free plan | Free plan | Web, Mac, Linux, API | 15 Oct 2026 |
| 09 Materialize | Materialize suits teams building applications or AI agents that need continually updated SQL views from connected data sources. | 5.3 | $1.50 a year | Free plan | Web, Linux, API, Self-hosted | 29 Sep 2026 |
| 10 Apache Hadoop HDFS | HDFS suits teams managing large data sets on self-hosted clusters that prioritize batch processing or streaming throughput. | 5.2 | Free plan | Free plan | Windows, Linux, API, Self-hosted | 15 Oct 2026 |
The page is ordered by newest releases first. It uses figures makers publish and does not score entries.
Exasol suits organizations needing multi-departmental analytics, in-database machine learning or AI, or complex data integration and virtualization.
Helios suits teams that need a cloud database for transactional and analytical work, with multiple data models or AI workloads.
WebWindowsMac+3Apache Beam suits data and software developers building batch or streaming pipelines for supported execution back ends.
WebWindowsMac+3Starburst recommends Galaxy for organizations that do not yet have resources to manage complex data clusters.
WebLinuxAPIIt is aimed at teams that need governed data products and controlled access across analytics and AI use.
PrestoDB is for users who need to run distributed SQL queries across heterogeneous data sources and can manage a self-hosted deployment.
Materialize suits teams building applications or AI agents that need continually updated SQL views from connected data sources.
HDFS suits teams managing large data sets on self-hosted clusters that prioritize batch processing or streaming throughput.
It suits enterprises with demanding analytics workloads and data residency or security requirements.
Apache Hive suits teams managing large datasets with SQL and connecting warehouse clients, storage, and related tools.
Apache Storm is for developers and teams building self-hosted systems that process ongoing data streams.
Druid may suit teams building low-latency analytics for streaming or batch data, especially workloads involving high query concurrency or immediate visibility into…
Spark suits teams and developers working with large-scale analytics, batch jobs, or real-time streams.
Kylin suits teams building analytics systems that use SQL models, streaming or batch data, and supported BI tools.
Impala suits teams running SQL-based analytics on Hadoop ecosystem data, including multitenant deployments.
Firebolt suits engineers choosing between self-managed analytical database deployments and a managed service, including teams working with open storage standards.
Trino suits teams that need SQL analytics across multiple data sources in cloud or on-premises environments.
Pinot suits teams building real-time analytics or user-facing workloads that combine batch and streaming data.
Flink suits teams building event-driven systems, stream or batch analytics, and data pipelines, especially those able to operate self-hosted cluster deployments.
Samza suits developers building real-time data applications who can manage a self-hosted framework.
Compare the Paid from field with free-plan availability. A free plan appears on items such as Apache Beam, Apache Doris and Apache Flink, while Amazon EMR with Apache HBase is marked paid.
A free trial is offered by items on this list. Check the product entry for its trial terms before choosing a paid path.
Open-source code is offered by items on this list. Pricing notes identify open-source offerings, including Apache Beam, Apache Druid, Apache Hive and Apache Kylin.
If you need to read or change code, check the licence details for the tool you are considering.
The platform field covers API, self-hosted, web, Linux, macOS and Windows deployments. Match that field to the environment where you plan to run the software.
Amazon EMR with Apache HBase is listed with web support. Check the entry for platform details before planning deployment.
Use the processing model and documented data scale fields to compare how a tool handles your workload. Review data source connectors when your data arrives from several systems.
Built-in visualization and query languages can affect how you explore results. Compare those fields with the way your team reads and presents data.