Alternatives to Apache Doris
Compare Apache Doris alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Apache Doris in 2026. Compare features, ratings, user reviews, pricing, and more from Apache Doris competitors and alternatives in order to make an informed decision for your business.
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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
Google Cloud BigQuery
Google
BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process. -
3
StarTree
StarTree
StarTree, powered by Apache Pinot™, is a fully managed real-time analytics platform built for customer-facing applications that demand instant insights on the freshest data. Unlike traditional data warehouses or OLTP databases—optimized for back-office reporting or transactions—StarTree is engineered for real-time OLAP at true scale, meaning: - Data Volume: query performance sustained at petabyte scale - Ingest Rates: millions of events per second, continuously indexed for freshness - Concurrency: thousands to millions of simultaneous users served with sub-second latency With StarTree, businesses deliver always-fresh insights at interactive speed, enabling applications that personalize, monitor, and act in real time.Starting Price: Free -
4
Amazon Redshift
Amazon
Amazon Redshift is a cloud-based data warehouse solution from AWS designed to deliver high-performance analytics and support modern AI-driven workloads. The platform enables organizations to analyze large volumes of structured and unstructured data across data warehouses, data lakes, and third-party sources using SQL. Redshift is built for scalability and cost efficiency, offering improved throughput and price-performance with AWS Graviton-powered RG instances and Redshift Serverless options. The solution also supports near real-time analytics through zero-ETL integrations that connect operational databases, streaming services, and enterprise applications without complex data pipelines. Amazon Redshift integrates with Amazon SageMaker and Amazon Bedrock to support advanced machine learning, analytics, and generative AI use cases.Starting Price: $0.543 per hour -
5
Oxla
Oxla
Purpose-built for compute, memory, and storage efficiency, Oxla is a self-hosted data warehouse optimized for large-scale, low-latency analytics with robust time-series support. Cloud data warehouses aren’t for everyone. At scale, long-term cloud compute costs outweigh short-term infrastructure savings, and regulated industries require full control over data beyond VPC and BYOC deployments. Oxla outperforms both legacy and cloud warehouses through efficiency, enabling scale for growing datasets with predictable costs, on-prem or in any cloud. Easily deploy, run, and maintain Oxla with Docker and YAML to power diverse workloads in a single, self-hosted data warehouse.Starting Price: $50 per CPU core / monthly -
6
SelectDB
SelectDB
SelectDB is a modern data warehouse based on Apache Doris, which supports rapid query analysis on large-scale real-time data. From Clickhouse to Apache Doris, to achieve the separation of the lake warehouse and upgrade to the lake warehouse. The fast-hand OLAP system carries nearly 1 billion query requests every day to provide data services for multiple scenes. Due to the problems of storage redundancy, resource seizure, complicated governance, and difficulty in querying and adjustment, the original lake warehouse separation architecture was decided to introduce Apache Doris lake warehouse, combined with Doris's materialized view rewriting ability and automated services, to achieve high-performance data query and flexible data governance. Write real-time data in seconds, and synchronize flow data from databases and data streams. Data storage engine for real-time update, real-time addition, and real-time pre-polymerization.Starting Price: $0.22 per hour -
7
Databend
Databend
Databend is a modern, cloud-native data warehouse built to deliver high-performance, cost-efficient analytics for large-scale data processing. It is designed with an elastic architecture that scales dynamically to meet the demands of different workloads, ensuring efficient resource utilization and lower operational costs. Written in Rust, Databend offers exceptional performance through features like vectorized query execution and columnar storage, which optimize data retrieval and processing speeds. Its cloud-first design enables seamless integration with cloud platforms, and it emphasizes reliability, data consistency, and fault tolerance. Databend is an open source solution, making it a flexible and accessible choice for data teams looking to handle big data analytics in the cloud.Starting Price: Free -
8
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. -
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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. -
10
Databricks
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. -
11
Materialize
Materialize
Materialize is a reactive database that delivers incremental view updates. We help developers easily build with streaming data using standard SQL. Materialize can connect to many different external sources of data without pre-processing. Connect directly to streaming sources like Kafka, Postgres databases, CDC, or historical sources of data like files or S3. Materialize allows you to query, join, and transform data sources in standard SQL - and presents the results as incrementally-updated Materialized views. Queries are maintained and continually updated as new data streams in. With incrementally-updated views, developers can easily build data visualizations or real-time applications. Building with streaming data can be as simple as writing a few lines of SQL.Starting Price: $0.98 per hour -
12
Apache Pinot
Apache Corporation
Pinot is designed to answer OLAP queries with low latency on immutable data. Pluggable indexing technologies - Sorted Index, Bitmap Index, Inverted Index. Joins are currently not supported, but this problem can be overcome by using Trino or PrestoDB for querying. SQL like language that supports selection, aggregation, filtering, group by, order by, distinct queries on data. Consist of of both offline and real-time table. Use real-time table only to cover segments for which offline data may not be available yet. Detect the right anomalies by customizing anomaly detect flow and notification flow. -
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Kinetica
Kinetica
A scalable cloud database for real-time analysis on large and streaming datasets. Kinetica is designed to harness modern vectorized processors to be orders of magnitude faster and more efficient for real-time spatial and temporal workloads. Track and gain intelligence from billions of moving objects in real-time. Vectorization unlocks new levels of performance for analytics on spatial and time series data at scale. Ingest and query at the same time to act on real-time events. Kinetica's lockless architecture and distributed ingestion ensures data is available to query as soon as it lands. Vectorized processing enables you to do more with less. More power allows for simpler data structures, which lead to lower storage costs, more flexibility and less time engineering your data. Vectorized processing opens the door to amazingly fast analytics and detailed visualization of moving objects at scale. -
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SingleStore
SingleStore
SingleStore (formerly MemSQL) is a distributed, highly-scalable SQL database that can run anywhere. We deliver maximum performance for transactional and analytical workloads with familiar relational models. SingleStore is a scalable SQL database that ingests data continuously to perform operational analytics for the front lines of your business. Ingest millions of events per second with ACID transactions while simultaneously analyzing billions of rows of data in relational SQL, JSON, geospatial, and full-text search formats. SingleStore delivers ultimate data ingestion performance at scale and supports built in batch loading and real time data pipelines. SingleStore lets you achieve ultra fast query response across both live and historical data using familiar ANSI SQL. Perform ad hoc analysis with business intelligence tools, run machine learning algorithms for real-time scoring, perform geoanalytic queries in real time.Starting Price: $0.69 per hour -
15
StarRocks
StarRocks
Whether you're working with a single table or multiple, you'll experience at least 300% better performance on StarRocks compared to other popular solutions. From streaming data to data capture, with a rich set of connectors, you can ingest data into StarRocks in real time for the freshest insights. A query engine that adapts to your use cases. Without moving your data or rewriting SQL, StarRocks provides the flexibility to scale your analytics on demand with ease. StarRocks enables a rapid journey from data to insight. StarRocks' performance is unmatched and provides a unified OLAP solution covering the most popular data analytics scenarios. Whether you're working with a single table or multiple, you'll experience at least 300% better performance on StarRocks compared to other popular solutions. StarRocks' built-in memory-and-disk-based caching framework is specifically designed to minimize the I/O overhead of fetching data from external storage to accelerate query performance.Starting Price: Free -
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Imply
Imply
Imply is a real-time analytics platform built on Apache Druid, designed to handle large-scale, high-performance OLAP (Online Analytical Processing) workloads. It offers real-time data ingestion, fast query performance, and the ability to perform complex analytical queries on massive datasets with low latency. Imply is tailored for organizations that need interactive analytics, real-time dashboards, and data-driven decision-making at scale. It provides a user-friendly interface for data exploration, along with advanced features such as multi-tenancy, fine-grained access controls, and operational insights. With its distributed architecture and scalability, Imply is well-suited for use cases in streaming data analytics, business intelligence, and real-time monitoring across industries. -
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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. -
18
Timeplus
Timeplus
Timeplus is a simple, powerful, and cost-efficient stream processing platform. All in a single binary, easily deployed anywhere. We help data teams process streaming and historical data quickly and intuitively, in organizations of all sizes and industries. Lightweight, single binary, without dependencies. End-to-end analytic streaming and historical functionalities. 1/10 the cost of similar open source frameworks. Turn real-time market and transaction data into real-time insights. Leverage append-only streams and key-value streams to monitor financial data. Implement real-time feature pipelines using Timeplus. One platform for all infrastructure logs, metrics, and traces, the three pillars supporting observability. In Timeplus, we support a wide range of data sources in our web console UI. You can also push data via REST API, or create external streams without copying data into Timeplus.Starting Price: $199 per month -
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Exasol
Exasol
With an in-memory, columnar database and MPP architecture, you can query billions of rows in seconds. Queries are distributed across all nodes in a cluster, providing linear scalability for more users and advanced analytics. MPP, in-memory, and columnar storage add up to the fastest database built for data analytics. With SaaS, cloud, on premises and hybrid deployment options you can analyze data wherever it lives. Automatic query tuning reduces maintenance and overhead. Seamless integrations and performance efficiency gets you more power at a fraction of normal infrastructure costs. Smart, in-memory query processing allowed this social networking company to boost performance, processing 10B data sets a year. A single data repository and speed engine to accelerate critical analytics, delivering improved patient outcome and bottom line. -
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Arroyo
Arroyo
Scale from zero to millions of events per second. Arroyo ships as a single, compact binary. Run locally on MacOS or Linux for development, and deploy to production with Docker or Kubernetes. Arroyo is a new kind of stream processing engine, built from the ground up to make real-time easier than batch. Arroyo was designed from the start so that anyone with SQL experience can build reliable, efficient, and correct streaming pipelines. Data scientists and engineers can build end-to-end real-time applications, models, and dashboards, without a separate team of streaming experts. Transform, filter, aggregate, and join data streams by writing SQL, with sub-second results. Your streaming pipelines shouldn't page someone just because Kubernetes decided to reschedule your pods. Arroyo is built to run in modern, elastic cloud environments, from simple container runtimes like Fargate to large, distributed deployments on the Kubernetes logo Kubernetes. -
21
Infobright DB
IgniteTech
Infobright DB is a high-performance enterprise database leveraging a columnar storage engine to enable business analysts to dissect data efficiently and more quickly obtain reports. InfoBright DB can be deployed on-premise or in the cloud. Store & analyze big data for interactive business intelligence and complex queries. Improve query performance, reduce storage cost and increase overall efficiency in business analytics and reporting. Easily store up to several hundred TB of data — traditionally not achievable with conventional databases. Run big data applications and eliminate indexing and partitioning — with zero administrative overhead. With the volumes of machine data exploding, IgniteTech’s Infobright DB is specifically designed to achieve high performance for large volumes of machine-generated data. Manage a complex ad hoc analytic environments without the database administration required by other products. -
22
Apache Kylin
Apache Software Foundation
Apache Kylin™ is an open source, distributed Analytical Data Warehouse for Big Data; it was designed to provide OLAP (Online Analytical Processing) capability in the big data era. By renovating the multi-dimensional cube and precalculation technology on Hadoop and Spark, Kylin is able to achieve near constant query speed regardless of the ever-growing data volume. Reducing query latency from minutes to sub-second, Kylin brings online analytics back to big data. Kylin can analyze 10+ billions of rows in less than a second. No more waiting on reports for critical decisions. Kylin connects data on Hadoop to BI tools like Tableau, PowerBI/Excel, MSTR, QlikSense, Hue and SuperSet, making the BI on Hadoop faster than ever. As an Analytical Data Warehouse, Kylin offers ANSI SQL on Hadoop/Spark and supports most ANSI SQL query functions. Kylin can support thousands of interactive queries at the same time, thanks to the low resource consumption of each query. -
23
Aerospike
Aerospike
Aerospike is the global leader in next-generation, real-time NoSQL data solutions for any scale. Aerospike enterprises overcome seemingly impossible data bottlenecks to compete and win with a fraction of the infrastructure complexity and cost of legacy NoSQL databases. Aerospike’s patented Hybrid Memory Architecture™ delivers an unbreakable competitive advantage by unlocking the full potential of modern hardware, delivering previously unimaginable value from vast amounts of data at the edge, to the core and in the cloud. Aerospike empowers customers to instantly fight fraud; dramatically increase shopping cart size; deploy global digital payment networks; and deliver instant, one-to-one personalization for millions of customers. Aerospike customers include Airtel, Banca d’Italia, Nielsen, PayPal, Snap, Verizon Media and Wayfair. The company is headquartered in Mountain View, Calif., with additional locations in London; Bengaluru, India; and Tel Aviv, Israel. -
24
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/credit -
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Azure Synapse Analytics
Microsoft
Azure Synapse is Azure SQL Data Warehouse evolved. Azure Synapse is a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless or provisioned resources—at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs. -
26
Hydra
Hydra
Hydra is an open source, column-oriented Postgres. Query billions of rows instantly, no code changes. Hydra parallelizes and vectorizes aggregates (COUNT, SUM, AVG) to deliver the speed you’ve always wanted on Postgres. Boost performance at every size! Set up Hydra in 5 minutes without changing your syntax, tools, data model, or extensions. Use Hydra Cloud for fully managed operations and smooth sailing. Different industries have different needs. Get better analytics with powerful Postgres extensions, custom functions, and take control. Built by you, for you. Hydra is the fastest Postgres in the market for analytics. Boost performance with columnar storage, vectorization, and query parallelization. -
27
IBM Db2
IBM
IBM Db2 is a family of data management products, including the Db2 relational database. The products feature AI-powered capabilities to help you modernize the management of both structured and unstructured data across on-premises and multicloud environments. By helping to make your data simple and accessible, the Db2 family positions your business to pursue the value of AI. Most of the Db2 family is available on the IBM Cloud Pak® for Data platform, either as an add-on or an included data source service, making virtually all of your data available across hybrid or multicloud environments to fuel your AI applications. Easily converge your transactional data stores and rapidly derive insights through universal, intelligent querying of data across disparate sources. Cut costs with the multimodel capability that eliminates the need for data replication and migration. Enhance agility by running Db2 on any cloud vendor. -
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Firebolt
Firebolt Analytics
Firebolt delivers extreme speed and elasticity at any scale solving your impossible data challenges. Firebolt has completely redesigned the cloud data warehouse to deliver a super fast, incredibly efficient analytics experience at any scale. An order-of-magnitude leap in performance means you can analyze much more data at higher granularity with lightning fast queries. Easily scale up or down to support any workload, amount of data and concurrent users. At Firebolt we believe that data warehouses should be much easier to use than what we’re used to. That's why we focus on turning everything that used to be complicated and labor intensive into simple tasks. Cloud data warehouse providers profit from the cloud resources you consume. We don’t! Finally, a pricing model that is fair, transparent, and allows you to scale without breaking the bank. -
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Presto
Presto Foundation
Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes. For data engineers who struggle with managing multiple query languages and interfaces to siloed databases and storage, Presto is the fast and reliable engine that provides one simple ANSI SQL interface for all your data analytics and your open lakehouse. Different engines for different workloads means you will have to re-platform down the road. With Presto, you get 1 familar ANSI SQL language and 1 engine for your data analytics so you don't need to graduate to another lakehouse engine. Presto can be used for interactive and batch workloads, small and large amounts of data, and scales from a few to thousands of users. Presto gives you one simple ANSI SQL interface for all of your data in various siloed data systems, helping you join your data ecosystem together. -
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Dremio
Dremio
Dremio delivers lightning-fast queries and a self-service semantic layer directly on your data lake storage. No moving data to proprietary data warehouses, no cubes, no aggregation tables or extracts. Just flexibility and control for data architects, and self-service for data consumers. Dremio technologies like Data Reflections, Columnar Cloud Cache (C3) and Predictive Pipelining work alongside Apache Arrow to make queries on your data lake storage very, very fast. An abstraction layer enables IT to apply security and business meaning, while enabling analysts and data scientists to explore data and derive new virtual datasets. Dremio’s semantic layer is an integrated, searchable catalog that indexes all of your metadata, so business users can easily make sense of your data. Virtual datasets and spaces make up the semantic layer, and are all indexed and searchable. -
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Tiger Data
Tiger Data
Tiger Data is the creator of TimescaleDB, the world’s leading PostgreSQL-based time-series and analytics database. It provides a modern data platform purpose-built for developers, devices, and AI agents. Designed to extend PostgreSQL beyond traditional limits, Tiger Data offers built-in primitives for time-series data, search, materialization, and scale. With features like auto-partitioning, hybrid storage, and compression, it helps teams query billions of rows in milliseconds while cutting infrastructure costs. Tiger Cloud delivers these capabilities as a fully managed, elastic environment with enterprise-grade security and compliance. Trusted by innovators like Cloudflare, Toyota, Polymarket, and Hugging Face, Tiger Data powers real-time analytics, observability, and intelligent automation across industries.Starting Price: $30 per month -
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QuestDB
QuestDB
QuestDB is a relational column-oriented database designed for time series and event data. It uses SQL with extensions for time series to assist with real-time analytics. These pages cover core concepts of QuestDB, including setup steps, usage guides, and reference documentation for syntax, APIs and configuration. This section describes the architecture of QuestDB, how it stores and queries data, and introduces features and capabilities unique to the system. Designated timestamp is a core feature that enables time-oriented language capabilities and partitioning. Symbol type makes storing and retrieving repetitive strings efficient. Storage model describes how QuestDB stores records and partitions within tables. Indexes can be used for faster read access on specific columns. Partitions can be used for significant performance benefits on calculations and queries. SQL extensions allow performant time series analysis with a concise syntax. -
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Onehouse
Onehouse
The only fully managed cloud data lakehouse designed to ingest from all your data sources in minutes and support all your query engines at scale, for a fraction of the cost. Ingest from databases and event streams at TB-scale in near real-time, with the simplicity of fully managed pipelines. Query your data with any engine, and support all your use cases including BI, real-time analytics, and AI/ML. Cut your costs by 50% or more compared to cloud data warehouses and ETL tools with simple usage-based pricing. Deploy in minutes without engineering overhead with a fully managed, highly optimized cloud service. Unify your data in a single source of truth and eliminate the need to copy data across data warehouses and lakes. Use the right table format for the job, with omnidirectional interoperability between Apache Hudi, Apache Iceberg, and Delta Lake. Quickly configure managed pipelines for database CDC and streaming ingestion. -
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Cloudera Data Warehouse
Cloudera
Cloudera Data Warehouse is a cloud-native, self-service analytics solution that lets IT rapidly deliver query capabilities to BI analysts, enabling users to go from zero to query in minutes. It supports all data types, structured, semi-structured, unstructured, real-time, and batch, and scales cost-effectively from gigabytes to petabytes. It is fully integrated with streaming, data engineering, and AI services, and enforces a unified security, governance, and metadata framework across private, public, or hybrid cloud deployments. Each virtual warehouse (data warehouse or mart) is isolated and automatically configured and optimized, ensuring that workloads do not interfere with each other. Cloudera leverages open source engines such as Hive, Impala, Kudu, and Druid, along with tools like Hue and more, to handle diverse analytics, from dashboards and operational analytics to research and discovery over vast event or time-series data. -
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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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DeltaStream
DeltaStream
DeltaStream is a unified serverless stream processing platform that integrates with streaming storage services. Think about it as the compute layer on top of your streaming storage. It provides functionalities of streaming analytics(Stream processing) and streaming databases along with additional features to provide a complete platform to manage, process, secure and share streaming data. DeltaStream provides a SQL based interface where you can easily create stream processing applications such as streaming pipelines, materialized views, microservices and many more. It has a pluggable processing engine and currently uses Apache Flink as its primary stream processing engine. DeltaStream is more than just a query processing layer on top of Kafka or Kinesis. It brings relational database concepts to the data streaming world, including namespacing and role based access control enabling you to securely access, process and share your streaming data regardless of where they are stored. -
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Trino
Trino
Trino is a query engine that runs at ludicrous speed. Fast-distributed SQL query engine for big data analytics that helps you explore your data universe. Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low-latency analytics. The largest organizations in the world use Trino to query exabyte-scale data lakes and massive data warehouses alike. Supports diverse use cases, ad-hoc analytics at interactive speeds, massive multi-hour batch queries, and high-volume apps that perform sub-second queries. Trino is an ANSI SQL-compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset, and many others. You can natively query data in Hadoop, S3, Cassandra, MySQL, and many others, without the need for complex, slow, and error-prone processes for copying the data. Access data from multiple systems within a single query.Starting Price: Free -
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BigObject
BigObject
At the heart of our innovation is in-data computing, a technology designed to process large amounts of data efficiently. Our flagship product, BigObject, embodies this core technology; it’s a time series database developed with the goal of high-speed storage and handling of massive data. With our core technology of in-data computing, we launched BigObject, which can quickly and continuously handle non-stop and all aspects of data streams. BigObject is a time series database developed with the goal of high-speed storage and analysis of massive data. It boasts excellent performance and powerful complex query capabilities. Extending the relational data structure to a time-series model structure, it utilizes in-data computing to optimize the database’s performance. Our core technology is an abstract model in which all data is kept in an infinite and persistent memory space for both storage and computing. -
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Google Cloud Datastream
Google
Serverless and easy-to-use change data capture and replication service. Access to streaming data from MySQL, PostgreSQL, AlloyDB, SQL Server, and Oracle databases. Near real-time analytics in BigQuery. Easy-to-use setup with built-in secure connectivity for faster time-to-value. A serverless platform that automatically scales, with no resources to provision or manage. Log-based mechanism to reduce the load and potential disruption on source databases. Synchronize data across heterogeneous databases, storage systems, and applications reliably, with low latency, while minimizing impact on source performance. Get up and running fast with a serverless and easy-to-use service that seamlessly scales up or down, and has no infrastructure to manage. Connect and integrate data across your organization with the best of Google Cloud services like BigQuery, Spanner, Dataflow, and Data Fusion. -
40
Google Cloud Lakehouse
Google
Google Cloud Lakehouse is a storage engine designed to unify data warehouses and data lakes into a single, cohesive platform. It allows organizations to access and manage data in open formats such as Apache Iceberg, Parquet, and ORC. The platform enables users to work with a single copy of data without needing to duplicate or move it across systems. It provides fine-grained security controls to ensure proper data governance and access management. Google Cloud Lakehouse simplifies data operations by integrating analytics and storage capabilities. It supports modern data workflows, including big data processing and analytics. The platform is built to scale with enterprise data needs while maintaining performance and flexibility. Overall, it helps organizations streamline data management and unlock insights more efficiently.Starting Price: $5 per TB -
41
Vertica
Rocket Software
Vertica is an enterprise-grade analytics database platform designed to help organizations run high-performance analytics, data warehousing, and AI workloads across hybrid cloud environments. Following its acquisition by Rocket Software, Vertica now strengthens Rocket’s modernization and enterprise data portfolio by combining advanced analytics, AI capabilities, and trusted mission-critical systems. The platform enables businesses to process and analyze massive volumes of structured and unstructured data while supporting on-premises, cloud, private cloud, and hybrid deployments. Vertica helps enterprises accelerate decision-making, modernize legacy environments, and run advanced analytics and generative AI directly on trusted enterprise data sources. The platform integrates with Rocket DataEdge and Rocket ContentEdge solutions to create a unified data modernization ecosystem focused on governance, analytics, and operational intelligence. -
42
Actian Data Platform
Actian
Actian Data Platform is a unified data management solution designed to simplify integration, storage, and analytics across hybrid environments. It combines data integration, data warehousing, and analytics capabilities into a single platform. The system enables organizations to connect and manage data from multiple sources using pre-built connectors and APIs. It supports real-time analytics, allowing users to gain insights from fresh data without performance delays. The platform uses advanced columnar storage and vectorized processing to deliver high-speed data performance. It also includes built-in data quality monitoring to ensure accuracy and reliability. Actian Data Platform can be deployed across on-premises, cloud, or hybrid environments for flexibility. By consolidating multiple tools into one system, it helps organizations reduce complexity and improve data-driven decision-making. -
43
Apache Flume
Apache Software Foundation
Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault-tolerant with tunable reliability mechanisms and many failovers and recovery mechanisms. It uses a simple extensible data model that allows for online analytic applications. The Apache Flume team is pleased to announce the release of Flume 1.8.0. Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of streaming event data. -
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R2 SQL
Cloudflare
R2 SQL is Cloudflare’s serverless, distributed analytics query engine (currently in open beta) that enables you to run SQL queries over Apache Iceberg tables stored in R2 Data Catalog without needing to manage your own compute clusters. It is built to efficiently query large volumes of data by leveraging metadata pruning, partition-level statistics, file and row-group filtering, and Cloudflare’s globally distributed compute infrastructure to parallelize execution. The system works by integrating with R2 object storage and an Iceberg catalog layer, so you can ingest data via Cloudflare Pipelines into Iceberg tables, and then query that data with minimal overhead. Queries can be issued via the Wrangler CLI or HTTP API (with an API token granting permissions across R2 SQL, Data Catalog, and storage). During the open beta period, using R2 SQL itself is not billed, only storage and standard R2 operations incur charges.Starting Price: Free -
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Citus
Citus Data
Citus gives you the Postgres you love, plus the superpower of distributed tables. 100% open source. Now with schema-based and row-based sharding, plus Postgres 16 support. Scale Postgres by distributing data & queries. You can start with a single Citus node, then add nodes & rebalance shards when you need to grow. Speed up queries by 20x to 300x (or more) through parallelism, keeping more data in memory, higher I/O bandwidth, and columnar compression. Citus is an extension (not a fork) to the latest Postgres versions, so you can use your familiar SQL toolset & leverage your Postgres expertise. Reduce your infrastructure headaches by using a single database for both your transactional and analytical workloads. Download and use Citus open source for free. You can manage Citus yourself, embrace open source, and help us improve Citus via GitHub. Focus on your application & forget about your database. Run your app on Citus in the cloud with Azure Cosmos DB for PostgreSQL.Starting Price: $0.27 per hour -
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Statsbot
Statsbot
Connect your database, let Statsbot generate data relationships from your database automatically, and get your first insights in a matter of minutes. Statsbot works with terabytes of raw data from hundreds of data sources. You don’t need to optimize or transform data beforehand. Define your transformations using SQL and Javascript. No need to learn proprietary languages or navigate complex interfaces. Data storage is cheap, but querying data is expensive. Statsbot makes your queries cost effective using a pre-aggregations layer on top of your data. Statsbot is designed to work with raw data stored in modern data warehouses. It not only queries and transforms data on the fly, it also does background jobs to optimize and pre-aggregate heavy calculations.By utilizing a transformation layer, Statsbot pre-aggregates heavy queries in the background. It makes even very complicated reports load blazingly fast.Starting Price: $39 per month -
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Decodable
Decodable
No more low level code and stitching together complex systems. Build and deploy pipelines in minutes with SQL. A data engineering service that makes it easy for developers and data engineers to build and deploy real-time data pipelines for data-driven applications. Pre-built connectors for messaging systems, storage systems, and database engines make it easy to connect and discover available data. For each connection you make, you get a stream to or from the system. With Decodable you can build your pipelines with SQL. Pipelines use streams to send data to, or receive data from, your connections. You can also use streams to connect pipelines together to handle the most complex processing tasks. Observe your pipelines to ensure data keeps flowing. Create curated streams for other teams. Define retention policies on streams to avoid data loss during external system failures. Real-time health and performance metrics let you know everything’s working.Starting Price: $0.20 per task per hour -
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Yellowbrick
Yellowbrick Data
Data Warehousing Without Limits While legacy platforms like Netezza struggle to stay relevant, and cloud-only options like Snowflake suffer from a reliance on VMs running on commodity hardware, Yellowbrick shatters ceilings on price/performance and deployment flexibility across on-premises and cloud environments. Pricing & Configurations. Performance Security. Get 100X Performance. Let thousands of users run ad hoc queries 10x-100x faster than any legacy or cloud-only data warehouse, on PBs of data. Plus, query real-time and at-rest data simultaneously. Deploy Anywhere Deploy applications everywhere — on-premises, in multiple public clouds, or both with the same data and performance everywhere (and no data egress charges). Save Millions Pay a fraction of what other options charge you via fixed-cost subscriptions for budget certainty, the more queries you run, the lower the cost per query. -
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Space and Time
Space and Time
Dapps built on top of Space and Time become blockchain interoperable, crunching SQL + machine learning for Gaming/DeFi data as well as any decentralized applications that need verifiable tamperproofing, blockchain-security, or enterprise scale. We merge blockchain data with a next-gen database by connecting off-chain storage with on-chain analytic insights. Join on-chain and off-chain data, making multi-chain integration, indexing, and anchoring data easy. Enabling advanced data security with mature and well-proven capabilities. Choose source data: connect to relational, realtime blockchain data we've already indexed from major chains as well as off-chain data you've ingested. Send tamperproof query results to smart contracts in a trustless way, or publish the query results directly on-chain using our novel cryptographic guarantees (Proof of SQL). -
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The Ocient Hyperscale Data Warehouse transforms and loads data in seconds, enables organizations to store and analyze more data, and executes queries on hyperscale datasets up to 50x faster. To deliver next-generation data analytics, Ocient completely reimagined its data warehouse design to deliver rapid, continuous analysis of complex, hyperscale datasets. The Ocient Hyperscale Data Warehouse brings storage adjacent to compute to maximize performance on industry-standard hardware, enables users to transform, stream or load data directly, and returns previously infeasible queries in seconds. Optimized for industry standard hardware, Ocient has benchmarked query performance levels up to 50x better than competing products. The Ocient Hyperscale Data Warehouse empowers next-generation data analytics solutions in key areas where existing solutions fall short.
