Alternatives to Tabular
Compare Tabular alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Tabular in 2026. Compare features, ratings, user reviews, pricing, and more from Tabular competitors and alternatives in order to make an informed decision for your business.
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1
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. -
2
Snowflake
Snowflake
Snowflake is a comprehensive AI Data Cloud platform designed to eliminate data silos and simplify data architectures, enabling organizations to get more value from their data. The platform offers interoperable storage that provides near-infinite scale and access to diverse data sources, both inside and outside Snowflake. Its elastic compute engine delivers high performance for any number of users, workloads, and data volumes with seamless scalability. Snowflake’s Cortex AI accelerates enterprise AI by providing secure access to leading large language models (LLMs) and data chat services. The platform’s cloud services automate complex resource management, ensuring reliability and cost efficiency. Trusted by over 11,000 global customers across industries, Snowflake helps businesses collaborate on data, build data applications, and maintain a competitive edge.Starting Price: $2 compute/month -
3
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 -
4
DuckDB
DuckDB
Processing and storing tabular datasets, e.g. from CSV or Parquet files. Large result set transfer to client. Large client/server installations for centralized enterprise data warehousing. Writing to a single database from multiple concurrent processes. DuckDB is a relational database management system (RDBMS). That means it is a system for managing data stored in relations. A relation is essentially a mathematical term for a table. Each table is a named collection of rows. Each row of a given table has the same set of named columns, and each column is of a specific data type. Tables themselves are stored inside schemas, and a collection of schemas constitutes the entire database that you can access. -
5
Apache Iceberg
Apache Software Foundation
Iceberg is a high-performance format for huge analytic tables. Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for engines like Spark, Trino, Flink, Presto, Hive and Impala to safely work with the same tables, at the same time. Iceberg supports flexible SQL commands to merge new data, update existing rows, and perform targeted deletes. Iceberg can eagerly rewrite data files for read performance, or it can use delete deltas for faster updates. Iceberg handles the tedious and error-prone task of producing partition values for rows in a table and skips unnecessary partitions and files automatically. No extra filters are needed for fast queries, and the table layout can be updated as data or queries change.Starting Price: Free -
6
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 -
7
BigLake
Google
BigLake is a storage engine that unifies data warehouses and lakes by enabling BigQuery and open-source frameworks like Spark to access data with fine-grained access control. BigLake provides accelerated query performance across multi-cloud storage and open formats such as Apache Iceberg. Store a single copy of data with uniform features across data warehouses & lakes. Fine-grained access control and multi-cloud governance over distributed data. Seamless integration with open-source analytics tools and open data formats. Unlock analytics on distributed data regardless of where and how it’s stored, while choosing the best analytics tools, open source or cloud-native over a single copy of data. Fine-grained access control across open source engines like Apache Spark, Presto, and Trino, and open formats such as Parquet. Performant queries over data lakes powered by BigQuery. Integrates with Dataplex to provide management at scale, including logical data organization.Starting Price: $5 per TB -
8
Amazon Athena
Amazon
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. Athena is easy to use. Simply point to your data in Amazon S3, define the schema, and start querying using standard SQL. Most results are delivered within seconds. With Athena, there’s no need for complex ETL jobs to prepare your data for analysis. This makes it easy for anyone with SQL skills to quickly analyze large-scale datasets. Athena is out-of-the-box integrated with AWS Glue Data Catalog, allowing you to create a unified metadata repository across various services, crawl data sources to discover schemas and populate your Catalog with new and modified table and partition definitions, and maintain schema versioning. -
9
FeatureByte
FeatureByte
FeatureByte is your AI data scientist streamlining the entire lifecycle so that what once took months now happens in hours. Deployed natively on Databricks, Snowflake, BigQuery, or Spark, it automates feature engineering, ideation, cataloging, custom UDFs (including transformer support), evaluation, selection, historical backfill, deployment, and serving (online or batch), all within a unified platform. FeatureByte’s GenAI‑inspired agents, data, domain, MLOps, and data science agents interactively guide teams through data acquisition, quality, feature generation, model creation, deployment orchestration, and continued monitoring. FeatureByte’s SDK and intuitive UI enable automated and semi‑automated feature ideation, customizable pipelines, cataloging, lineage tracking, approval flows, RBAC, alerts, and version control, empowering teams to build, refine, document, and serve features rapidly and reliably. -
10
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 -
11
Permify
Permify
Permify is an authorization service designed to help developers build and manage fine-grained, scalable access control systems within their applications. Inspired by Google's Zanzibar, Permify enables the structuring of authorization models, storage of authorization data in preferred databases, and interaction with its API to handle authorization queries across various applications and services. It supports multiple access control models, including Role-Based Access Control (RBAC), and Attribute-Based Access Control (ABAC), allowing for the creation of granular permissions and policies. Permify centralized authorization logic, abstracting it from the codebase to facilitate easier reasoning, testing, and debugging. It offers flexible policy storage options and provides a role manager to handle RBAC role hierarchies. The platform also supports filtered policy management for efficient enforcement in large, multi-tenant environments.Starting Price: Free -
12
Mitzu
Mitzu.io
Mitzu.io is a warehouse-native analytics platform designed for SaaS and e-commerce businesses. It enables teams to derive actionable insights directly from their data warehouses or lakes without complex data modeling or copying data into third-party systems. The platform integrates seamlessly with popular data storage solutions like Snowflake, BigQuery, Redshift, Databricks, and Trino. Mitzu's key feature is its capability to provide self-service analytics. It empowers non-technical users like product managers, marketers, and sales teams to explore data and generate insights without SQL expertise. The platform automatically generates SQL queries based on user interactions, providing real-time analytics for monitoring user behavior, feature usage, and engagement patterns. One of Mitzu's main advantages is that it works directly on raw datasets in the warehouse, eliminating the need for data duplication. Also, it works with seat-based pricing! Cheaper than the alternatives.Starting Price: $95 per month -
13
nao
nao
nao is an AI-powered data IDE designed specifically for data teams, combining a code editor with native integration to your data warehouse so you can write, test, and maintain data-centric code with full context. It supports warehouses such as Postgres, Snowflake, BigQuery, Databricks, DuckDB, Motherduck, Athena, and Redshift. Once connected, nao replaces a traditional data-warehouse console by offering schema-aware SQL auto-completion, data previews, SQL worksheets, and the ability to switch easily between multiple warehouses. The core of nao is its AI agent, which has full awareness of your actual data schema, tables, columns, metadata, and your codebase or data-stack context. It can generate SQL queries or full data-transformation models (e.g., for dbt workflows), refactor code, add or update documentation, run data-quality checks and data-diff tests, and even surface insights or run exploratory analytics, all while respecting data structure and quality constraints.Starting Price: $30 per month -
14
Qvu Data Service
rbtdesign
Qvu Data Service is an ad-hoc query and api data service design tool that allows users to create and save query designs in a user-friendly, web-based UI. Qvu Data Service provides REST API endpoints for users and applications to execute saved query documents and return results in tabular or JSON formatted result sets. Qvu Data Service provides role-based data source, table column and document group access control and supports both Basic and OIDC authentication.Starting Price: $0 -
15
RazorSQL
RazorSQL
RazorSQL is an SQL query tool, database browser, SQL editor, and database administration tool for Windows, macOS, Mac OS X, Linux, and Solaris. RazorSQL has been tested on over 40 databases, can connect to databases via either JDBC or ODBC. Browse database objects such as schemas, tables, columns, primary and foreign keys, views, indexes, procedures, functions, and more. Visual tools to create, alter, describe, execute, and drop database objects such as tables, views, indexes, stored procedures, functions, triggers, and more. Includes multi-tabular display of queries with options for filtering, sorting, searching, and much more. Import data from various formats such as delimited files, Excel spreadsheets, and fixed-width files. Includes a robust relational database (HSQLDB) that is up and running with no manual configuration out of the box.Starting Price: $99.95 one-time payment -
16
SSuite MonoBase Database
SSuite Office Software
Create relational or flat file databases with unlimited tables, fields, and rows. Includes a custom report builder. Interface with ODBC compatible databases and create custom reports for them. Create your own personal and custom databases. Some Highlights: - Filter tables instantly - Ultra simple graphical-user-interface - One click table and data form creation - Open up to 5 databases simultaneously - Export your data to comma separated files - Create custom reports for all your databases - Full helpfile to assist in creating database reports - Print tables and queries directly from the data grid - Supports any SQL standard that your ODBC compatible database requires Please install and run this database application with full administrator rights for best performance and user experience. Requires: . 1024x768 Display Size . Windows 98 / XP / 7 / 8 / 10 - 32bit and 64bit No Java or DotNet required. Green Energy Software. Saving the planet one bit at a time...Starting Price: Free -
17
Apache Impala
Apache
Impala provides low latency and high concurrency for BI/analytic queries on the Hadoop ecosystem, including Iceberg, open data formats, and most cloud storage options. Impala also scales linearly, even in multitenant environments. Impala is integrated with native Hadoop security and Kerberos for authentication, and via the Ranger module, you can ensure that the right users and applications are authorized for the right data. Utilize the same file and data formats and metadata, security, and resource management frameworks as your Hadoop deployment, with no redundant infrastructure or data conversion/duplication. For Apache Hive users, Impala utilizes the same metadata and ODBC driver. Like Hive, Impala supports SQL, so you don't have to worry about reinventing the implementation wheel. With Impala, more users, whether using SQL queries or BI applications, can interact with more data through a single repository and metadata stored from source through analysis.Starting Price: Free -
18
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. -
19
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. -
20
Baidu Palo
Baidu AI Cloud
Palo helps enterprises to create the PB-level MPP architecture data warehouse service within several minutes and import the massive data from RDS, BOS, and BMR. Thus, Palo can perform the multi-dimensional analytics of big data. Palo is compatible with mainstream BI tools. Data analysts can analyze and display the data visually and gain insights quickly to assist decision-making. It has the industry-leading MPP query engine, with column storage, intelligent index,and vector execution functions. It can also provide in-library analytics, window functions, and other advanced analytics functions. You can create a materialized view and change the table structure without the suspension of service. It supports flexible and efficient data recovery. -
21
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. -
22
Agile Data Engine
Agile Data Engine
Agile Data Engine is a comprehensive DataOps platform designed to streamline the development, deployment, and operation of cloud-based data warehouses. It integrates data modeling, transformations, continuous deployment, workflow orchestration, monitoring, and API connectivity within a single SaaS solution. The platform's metadata-driven approach automates SQL code generation and data load workflows, enhancing productivity and agility in data operations. Supporting multiple cloud database platforms, including Snowflake, Databricks SQL, Amazon Redshift, Microsoft Fabric (Warehouse), Azure Synapse SQL, Azure SQL Database, and Google BigQuery, Agile Data Engine offers flexibility in cloud environments. Its modular data product framework and out-of-the-box CI/CD pipelines facilitate seamless integration and continuous delivery, enabling data teams to adapt swiftly to changing business requirements. The platform also provides insights and statistics on data platform performance. -
23
SparkGrid
Sparksoft Corporation
SparkGrid is a user-friendly data management tool that simplifies communication with Snowflake by offering a tabularized interface similar to standard spreadsheet applications. It allows users to perform complex data tasks without needing extensive technical knowledge, making Snowflake more accessible. SparkGrid supports multi-field editing, SQL statement previews, and built-in error handling and security features to ensure data integrity. The intuitive graphical user interface enables easy navigation, selection, and manipulation of data such as adding or removing rows and columns. By bridging the gap between visual data management and SQL queries, SparkGrid empowers teams to work efficiently. It is designed to enhance productivity and democratize access to Snowflake’s powerful data capabilities. Available on AWS's marketplace, just search "Sparkgrid AWS Marketplace" Or contact us for custom implementation options.Starting Price: $0.20/hour -
24
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. -
25
NoSQL
NoSQL
NoSQL is a domain-specific programming language used for accessing, managing, and manipulating non-tabular databases. A NoSQL (originally referring to "non-SQL" or "non-relational") database provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases. Such databases have existed since the late 1960s, but the name "NoSQL" was only coined in the early 21st century, triggered by the needs of Web 2.0 companies. NoSQL databases are increasingly used in big data and real-time web applications.NoSQL systems are also sometimes called Not only SQL to emphasize that they may support SQL-like query languages or sit alongside SQL databases in polyglot-persistent architectures. Many NoSQL stores compromise consistency (in the sense of the CAP theorem) in favor of availability, partition tolerance, and speed. Barriers to the greater adoption of NoSQL stores include the use of low-level query languages. -
26
PuppyGraph
PuppyGraph
PuppyGraph empowers you to seamlessly query one or multiple data stores as a unified graph model. Graph databases are expensive, take months to set up, and need a dedicated team. Traditional graph databases can take hours to run multi-hop queries and struggle beyond 100GB of data. A separate graph database complicates your architecture with brittle ETLs and inflates your total cost of ownership (TCO). Connect to any data source anywhere. Cross-cloud and cross-region graph analytics. No complex ETLs or data replication is required. PuppyGraph enables you to query your data as a graph by directly connecting to your data warehouses and lakes. This eliminates the need to build and maintain time-consuming ETL pipelines needed with a traditional graph database setup. No more waiting for data and failed ETL processes. PuppyGraph eradicates graph scalability issues by separating computation and storage.Starting Price: Free -
27
CData Sync
CData Software
CData Sync is a universal data pipeline that delivers automated continuous replication between hundreds of SaaS applications & cloud data sources and any major database or data warehouse, on-premise or in the cloud. Replicate data from hundreds of cloud data sources to popular database destinations, such as SQL Server, Redshift, S3, Snowflake, BigQuery, and more. Configuring replication is easy: login, select the data tables to replicate, and select a replication interval. Done. CData Sync extracts data iteratively, causing minimal impact on operational systems by only querying and updating data that has been added or changed since the last update. CData Sync offers the utmost flexibility across full and partial replication scenarios and ensures that critical data is stored safely in your database of choice. Download a 30-day free trial of the Sync application or request more information at www.cdata.com/sync -
28
XmlPad
Semyon A. Chertkov
XmlPad is a professional editor for XML docs processing which allows presenting the data in tabular style. It includes a text editor with syntax highlighting, string numeration, collapsing and element autocompletion options. It is integrated with full-function table editor which considerably simplifies the documents processing at the tablet device. It maintains autoformatting and XML validation under the specified DTD, XSD, RelaxNG, and Schematron schemas while representing errors in the documents text at the same time. It allows to run XQuery queries and XSLT transforms. Built-in command console lets to run curl and base file commands. The table editor allows creating xml docs at several touches, it has a content panning function and is synchronized with document textual view.Starting Price: Free -
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Apache Drill
The Apache Software Foundation
Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage -
30
Azure Data Lake Storage
Microsoft
Eliminate data silos with a single storage platform. Optimize costs with tiered storage and policy management. Authenticate data using Azure Active Directory (Azure AD) and role-based access control (RBAC). And help protect data with security features like encryption at rest and advanced threat protection. Highly secure with flexible mechanisms for protection across data access, encryption, and network-level control. Single storage platform for ingestion, processing, and visualization that supports the most common analytics frameworks. Cost optimization via independent scaling of storage and compute, lifecycle policy management, and object-level tiering. Meet any capacity requirements and manage data with ease, with the Azure global infrastructure. Run large-scale analytics queries at consistently high performance. -
31
Amazon Timestream
Amazon
Amazon Timestream is a fast, scalable, and serverless time series database service for IoT and operational applications that makes it easy to store and analyze trillions of events per day up to 1,000 times faster and at as little as 1/10th the cost of relational databases. Amazon Timestream saves you time and cost in managing the lifecycle of time series data by keeping recent data in memory and moving historical data to a cost optimized storage tier based upon user defined policies. Amazon Timestream’s purpose-built query engine lets you access and analyze recent and historical data together, without needing to specify explicitly in the query whether the data resides in the in-memory or cost-optimized tier. Amazon Timestream has built-in time series analytics functions, helping you identify trends and patterns in your data in near real-time. -
32
PySpark
PySpark
PySpark is an interface for Apache Spark in Python. It not only allows you to write Spark applications using Python APIs, but also provides the PySpark shell for interactively analyzing your data in a distributed environment. PySpark supports most of Spark’s features such as Spark SQL, DataFrame, Streaming, MLlib (Machine Learning) and Spark Core. Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrame and can also act as distributed SQL query engine. Running on top of Spark, the streaming feature in Apache Spark enables powerful interactive and analytical applications across both streaming and historical data, while inheriting Spark’s ease of use and fault tolerance characteristics. -
33
Mason
Mason
Mason learns from every query you write. Seamlessly query, visualize and share data with your team. Generate SQL and tweak the result using our best-in-class AI assistant. Mason automatically recommends and completes your joins for you. Say goodbye to scrolling an endless list of tables. Connect securely to BigQuery, Snowflake, PostgreSQL, and Redshift. Everything you need to effectively collaborate with your team members. Review query versions. See who made changes. Restore to any point in time. Discover all your team's queries in the shared query library. Stay focused by visualizing your queries in team-specific dashboards. Get feedback directly in your code. Experience a data tool that doesn't waste your time. Discover, navigate, and perform any action from anywhere. Stay in the flow using keyboard shortcuts. Experience the fastest way to query, visualize, and share. Our realtime sync delivers more than 100ms interactions worldwide.Starting Price: $12 per month -
34
Motif Analytics
Motif Analytics
Rich interactive visualizations for identifying patterns in user and business flows, with full visibility into underlying computation. A small set of sequence operations providing full expressivity and fine-grained control in under 10 lines of code. An incremental query engine to seamlessly trade between query precision, speed and cost according to your needs. Currently Motif uses a tiny custom-built DSL called Sequence Operations Language (SOL), which we believe is more natural to use than SQL and more powerful than a drag-and-drop interface. We built a custom engine to optimize sequence queries and are also trading off precision, which goes unused in decision-making, for query speed. -
35
Tad
Tad
Tad is a free (MIT Licensed) desktop application for viewing and analyzing tabular data. It is a fast viewer for CSV and Parquet files and SQLite and DuckDb databases that support large files. It's a Pivot Table for analyzing and exploring data. Internally, Tad uses DuckDb for fast, accurate processing. Designed to fit into the workflow of data engineers and data scientists. Tad includes updates to DuckDb 1.0, the ability to export filtered tables as Parquet (as well as CSV), a fix for formatting numbers in scientific notation, and other minor bug fixes and dependent package upgrades. A packaged installer for Tad is available for macOS (x86 and Apple Silicon), Linux, and Windows.Starting Price: Free -
36
Text2SQL.AI
Text2SQL.AI
Generate SQL with AI in seconds. Turn your thoughts into complex SQL queries using natural language. Text2SQL.AI uses theOpenAI GPT-3 Codexmodel which can translate English prompts to SQL queries, and SQL queries to English text. It is currently the most advanced Natural Language Processing tool available, and this is the exact same model which used by Github Copilot. The app currently supports: SQL generation from English textual instructions. Supports SELECT, UPDATE, DELETE queries, CREATE and ALTER TABLE requests, constraints, window functions, and literally everything! SQL query explanation to plain English Your custom database schema (tables, fields, types) connection (with history) SQL dialects for MySQL, PostgreSQL, Snowflake, BigQuery, MS SQL Server... If you have any other feature request, please let us know. -
37
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. -
38
ksqlDB
Confluent
Now that your data is in motion, it’s time to make sense of it. Stream processing enables you to derive instant insights from your data streams, but setting up the infrastructure to support it can be complex. That’s why Confluent developed ksqlDB, the database purpose-built for stream processing applications. Make your data immediately actionable by continuously processing streams of data generated throughout your business. ksqlDB’s intuitive syntax lets you quickly access and augment data in Kafka, enabling development teams to seamlessly create real-time innovative customer experiences and fulfill data-driven operational needs. ksqlDB offers a single solution for collecting streams of data, enriching them, and serving queries on new derived streams and tables. That means less infrastructure to deploy, maintain, scale, and secure. With less moving parts in your data architecture, you can focus on what really matters -- innovation. -
39
Compass
Dagster Labs
Compass is an AI-powered, Slack-native data assistant that turns plain English questions into instant answers, summaries, charts, and insights powered by your actual warehouse data, so teams can make data-driven decisions without waiting on BI backlogs or building dashboards first. It connects directly to major data warehouses (Snowflake, BigQuery, Redshift, Postgres, AWS Athena, Databricks, and more), learns your schema and context, and generates governed, SQL-backed responses and visualizations in the tools your team already uses, all while keeping your data where it lives and under your control. Compass builds organizational context over time so answers become more accurate and relevant, supports collaboration through Slack threads, can schedule recurring analysis, and provides a shared repository of definitions and insights that help reduce analytical silos and reliance on specialized SQL users.Starting Price: $49 per month -
40
QuasarDB
QuasarDB
Quasar's brain is QuasarDB, a high-performance, distributed, column-oriented timeseries database management system designed from the ground up to deliver real-time on petascale use cases. Up to 20X less disk usage. Quasardb ingestion and compression capabilities are unmatched. Up to 10,000X faster feature extraction. QuasarDB can extract features in real-time from the raw data, thanks to the combination of a built-in map/reduce query engine, an aggregation engine that leverages SIMD from modern CPUs, and stochastic indexes that use virtually no disk space. The most cost-effective timeseries solution, thanks to its ultra-efficient resource usage, the capability to leverage object storage (S3), unique compression technology, and fair pricing model. Quasar runs everywhere, from 32-bit ARM devices to high-end Intel servers, from Edge Computing to the cloud or on-premises. -
41
Cazpian
Cazpian
Cazpian is a unified data platform designed for modern data teams working with open lakehouse architectures. The platform brings together data governance, compute environments, catalog management, and AI capabilities into a single system. Cazpian allows organizations to connect and query data across object storage, Iceberg tables, and relational databases through one SQL interface. Its unified catalog enables teams to manage data sources without moving or duplicating datasets. The platform also includes tools for scheduling jobs, running queries, and managing compute resources. Built-in AI agents provide evidence-backed insights and help teams analyze data more efficiently. By combining governance, analytics, and automation in one platform, Cazpian helps organizations manage large-scale data environments more effectively. -
42
TableBits
LENSELL
TableBits by LENSELL is a smart, time-saving tool that helps investors, administrators, and analysts extract tabular data from PDFs, like financial statements, in seconds. Designed with simplicity and clarity in mind, TableBits streamlines workflows by converting complex financial data into structured CSV files—no manual copying, no errors. TableBits offers a simpler way to work with financial documents—so you can focus more on what matters. For any enquiries contact us. -
43
Apache Hive
Apache Software Foundation
The Apache Hive data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command line tool and JDBC driver are provided to connect users to Hive. Apache Hive is an open source project run by volunteers at the Apache Software Foundation. Previously it was a subproject of Apache® Hadoop®, but has now graduated to become a top-level project of its own. We encourage you to learn about the project and contribute your expertise. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data. Hive provides the necessary SQL abstraction to integrate SQL-like queries (HiveQL) into the underlying Java without the need to implement queries in the low-level Java API. -
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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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Vanna.AI
Vanna.AI
Vanna.AI is an AI-powered platform designed to help users interact with their databases by asking questions in natural language. It enables both beginners and experts to quickly obtain insights from large datasets without needing to write complex SQL queries. Users simply ask a question, and Vanna automatically identifies the relevant tables and columns to retrieve the data needed. The platform integrates with popular databases like Snowflake, BigQuery, and Postgres and supports various front-end implementations such as Jupyter Notebooks, Slackbots, and web apps. Vanna's open source model allows for secure, self-hosted deployments and can continuously improve its performance as it learns from the user's interactions. It is ideal for businesses looking to democratize access to data insights and simplify the query process.Starting Price: $25 per month -
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SSAS
Microsoft
Installed as an on-premises server instance, SQL Server Analysis Services supports tabular models at all compatibility levels (depending on version), multidimensional models, data mining, and Power Pivot for SharePoint. A typical implementation workflow includes installing a SQL Server Analysis Services instance, creating a tabular or multidimensional data model, deploying the model as a database to a server instance, processing the database to load it with data, and then assigning permissions to allow data access. When ready to go, the data model can be accessed by any client application supporting Analysis Services as a data source. Models are populated with data from external data systems, usually data warehouses hosted on a SQL Server or Oracle relational database engine (Tabular models support additional data source types). -
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Armet AI
Fortanix
Armet AI is a secure, turnkey GenAI platform built on Confidential Computing that encloses every stage, from data ingestion and vectorization to LLM inference and response handling, within hardware-enforced secure enclaves. It delivers Confidential AI with Intel SGX, TDX, TiberTrust Services and NVIDIA GPUs to keep data encrypted at rest, in motion and in use; AI Guardrails that automatically sanitize sensitive inputs, enforce prompt security, detect hallucinations and uphold organizational policies; and Data & AI Governance with consistent RBAC, project-based collaboration frameworks, custom roles and centrally managed access controls. Its End-to-End Data Security ensures zero-trust encryption across storage, transit, and processing layers, while Holistic Compliance aligns with GDPR, the EU AI Act, SOC 2, and other industry standards to protect PII, PCI, and PHI. -
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Databricks Data Intelligence Platform
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
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Numbers Station
Numbers Station
Accelerating insights, eliminating barriers for data analysts. Intelligent data stack automation, get insights from your data 10x faster with AI. Pioneered at the Stanford AI lab and now available to your enterprise, intelligence for the modern data stack has arrived. Use natural language to get value from your messy, complex, and siloed data in minutes. Tell your data your desired output, and immediately generate code for execution. Customizable automation of complex data tasks that are specific to your organization and not captured by templated solutions. Empower anyone to securely automate data-intensive workflows on the modern data stack, free data engineers from an endless backlog of requests. Arrive at insights in minutes, not months. Uniquely designed for you, tuned for your organization’s needs. Integrated with upstream and downstream tools, Snowflake, Databricks, Redshift, BigQuery, and more coming, built on dbt. -
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PeerDB
PeerDB
If Postgres is at the core of your business and is a major source of data, PeerDB provides a fast, simple, and cost-effective way to replicate data from Postgres to data warehouses, queues, and storage. Designed to run at any scale, and tailored for data stores. PeerDB uses replication messages from the Postgres replication slot to replay the schema messages. Alerts for slot growth and connections. Native support for Postgres toast columns and large JSONB columns for IoT. Optimized query design to reduce warehouse costs; particularly useful for Snowflake and BigQuery. Support for partitioned tables via both publish. Blazing fast and consistent initial load by transaction snapshotting and CTID scans. High-availability, in-place upgrades, autoscaling, advance logs, metrics and monitoring dashboards, burstable instance types, and suitable for dev environments.Starting Price: $250 per month
