Alternatives to IBM Cloud SQL Query
Compare IBM Cloud SQL Query alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to IBM Cloud SQL Query in 2026. Compare features, ratings, user reviews, pricing, and more from IBM Cloud SQL Query 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
Apache DataFusion
Apache Software Foundation
Apache DataFusion is an extensible, high-performance query engine written in Rust that utilizes Apache Arrow as its in-memory format. Designed for developers building data-centric systems such as databases, data frames, machine learning, and streaming applications, DataFusion offers SQL and DataFrame APIs, a vectorized, multi-threaded, streaming execution engine, and support for partitioned data sources. It natively supports formats like CSV, Parquet, JSON, and Avro, and allows for seamless integration with object stores including AWS S3, Azure Blob Storage, and Google Cloud Storage. The engine features a comprehensive query planner, a state-of-the-art optimizer with capabilities like expression coercion and simplification, projection and filter pushdown, sort and distribution-aware optimizations, and automatic join reordering. DataFusion is highly customizable, enabling the addition of user-defined scalar, aggregate, and window functions, custom data sources, query languages, etc.Starting Price: Free -
3
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 -
4
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. -
5
Apache Phoenix
Apache Software Foundation
Apache Phoenix enables OLTP and operational analytics in Hadoop for low-latency applications by combining the best of both worlds. The power of standard SQL and JDBC APIs with full ACID transaction capabilities and the flexibility of late-bound, schema-on-read capabilities from the NoSQL world by leveraging HBase as its backing store. Apache Phoenix is fully integrated with other Hadoop products such as Spark, Hive, Pig, Flume, and Map Reduce. Become the trusted data platform for OLTP and operational analytics for Hadoop through well-defined, industry-standard APIs. Apache Phoenix takes your SQL query, compiles it into a series of HBase scans, and orchestrates the running of those scans to produce regular JDBC result sets. Direct use of the HBase API, along with coprocessors and custom filters, results in performance on the order of milliseconds for small queries, or seconds for tens of millions of rows.Starting Price: Free -
6
TimescaleDB
Tiger Data
TimescaleDB is the leading time-series database built on PostgreSQL, designed to handle massive volumes of real-time data efficiently. It enables organizations to store, analyze, and query time-series data — such as IoT sensor data, financial transactions, or event logs — using standard SQL. With hypertables, TimescaleDB automatically partitions data by time and ID for fast ingestion and predictable query performance. Its compression engine reduces storage costs by up to 95%, while continuous aggregates make real-time dashboards instantly responsive. Fully compatible with PostgreSQL, it integrates seamlessly with existing tools and applications. TimescaleDB combines the simplicity of Postgres with the scalability and speed of a specialized analytical system. -
7
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. -
8
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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IBM Db2 Big SQL
IBM
A hybrid SQL-on-Hadoop engine delivering advanced, security-rich data query across enterprise big data sources, including Hadoop, object storage and data warehouses. IBM Db2 Big SQL is an enterprise-grade, hybrid ANSI-compliant SQL-on-Hadoop engine, delivering massively parallel processing (MPP) and advanced data query. Db2 Big SQL offers a single database connection or query for disparate sources such as Hadoop HDFS and WebHDFS, RDMS, NoSQL databases, and object stores. Benefit from low latency, high performance, data security, SQL compatibility, and federation capabilities to do ad hoc and complex queries. Db2 Big SQL is now available in 2 variations. It can be integrated with Cloudera Data Platform, or accessed as a cloud-native service on the IBM Cloud Pak® for Data platform. Access and analyze data and perform queries on batch and real-time data across sources, like Hadoop, object stores and data warehouses. -
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Valentina Studio
Paradigma Software
Create, administer, query and explore Valentina DB, MySQL, MariaDB, PostgreSQL and SQLite databases for FREE. Design business reports running in Valentina Studio Pro, on Valentina Server or in an application with an Application Developer Kit. Backward Engineering in Standard with forwarding Engineering in Valentina Studio Pro. Reverse engineering and create diagrams for existing databases. Add new objects to diagrams. Write SQL queries with auto-completion, color syntax. Define, manage, save favorite queries; access recent queries. Function browser dictionary of each function. Consoles for errors, warnings, and performance. Search, Export result records into CSV, JSON, Excel. Edit properties of multiple objects at the same time. Drill down to tables and fields; incredible fast searching. Reverse engineering and create diagrams for existing databases. Add new objects to diagrams. Add/drop users, and groups, and manage privileges.Starting Price: $79 -
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CockroachDB
Cockroach Labs
CockroachDB: Cloud-native, distributed SQL. Your cloud applications deserve a cloud-native database. Cloud-based apps and services deserve a database that scales across clouds, eases operational complexity, and improves reliability. CockroachDB delivers resilient, distributed SQL with ACID transactions and data partitioned by location. Automate operations for mission-critical applications by pairing CockroachDB with orchestration tools like Kubernetes and Mesosphere DC/OS. Every node can service both reads and writes so that you can scale query throughput and database capacity by simply adding more endpoints. Just add new nodes to CockroachDB, and it automatically rebalances data, completely removing the pain of manual sharding. As demand shifts, CockroachDB detects hotspots and intelligently distributes data to maintain performance. Tune your database at the row level so that data lives close to your users and you can minimize query latency. -
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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. -
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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. -
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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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QueryPlus
QualCorp
QueryPlus© represents the next generation in insurance reporting. Taking your input, QueryPlus© dynamically writes complex SQL queries behind the scenes and then displays the results in a simple, familiar, and flexible grid format where data can be easily manipulated by simply dragging and dropping. From customer ranking reports to complex accounting reports, QueryPlus© allows you to get the critical business data you need quickly & efficiently. For those agencies with advanced reporting needs, QueryPlus© includes a customized report designer which allows you to create even the most complex reports using your custom dataset. Though the preferred format for data processing may often be that of Excel spreadsheets, QueryPlus© is also the tool of choice for those who want the most robust reporting features available. Providing a friendly, intuitive, visually-based, wizard-driven report design environment. -
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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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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 -
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HugeGraph
HugeGraph
HugeGraph is a fast-speed and highly-scalable graph database. Billions of vertices and edges can be easily stored into and queried from HugeGraph due to its excellent OLTP ability. As compliance to Apache TinkerPop 3 framework, various complicated graph queries can be accomplished through Gremlin (a powerful graph traversal language). Among its features, it provides compliance to Apache TinkerPop 3, supporting Gremlin. Schema Metadata Management, including VertexLabel, EdgeLabel, PropertyKey and IndexLabel. Multi-type Indexes, supporting exact query, range query and complex conditions combination query. Plug-in Backend Store Driver Framework, supporting RocksDB, Cassandra, ScyllaDB, HBase and MySQL now and easy to add other backend store driver if needed. Integration with Hadoop/Spark. HugeGraph relies on the TinkerPop framework, we refer to the storage structure of Titan and the schema definition of DataStax. -
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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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XTDB
XTDB
XTDB is an immutable SQL database designed to simplify application development and ensure data compliance. It automatically preserves data history, enabling comprehensive time-travel queries. Users can perform as-of queries and audits using SQL commands. XTDB is trusted by various companies to transform dynamic and temporal applications. It is easy to get started with via HTTP, plain SQL, or various programming languages, requiring only a client driver or Curl. Users can effortlessly insert data immutably, query it across time, and execute complex joins. Risk systems benefit directly from bitemporal modeling. Valid time can be used to correlate out-of-order trade data whilst making compliance easy. Exposing data across an organization is a challenge when things are changing all the time. XTDB simplifies data exchange and can power advanced temporal analysis. Modeling future pricing, tax, and discount changes requires extensive temporal queries. -
21
ZeusDB
ZeusDB
ZeusDB is a next-generation, high-performance data platform designed to handle the demands of modern analytics, machine learning, real-time insights, and hybrid data workloads. It supports vector, structured, and time-series data in one unified engine, allowing recommendation systems, semantic search, retrieval-augmented generation pipelines, live dashboards, and ML model serving to operate from a single store. The platform delivers ultra-low latency querying and real-time analytics, eliminating the need for separate databases or caching layers. Developers and data engineers can extend functionality with Rust or Python logic, deploy on-premises, hybrid, or cloud, and operate under GitOps/CI-CD patterns with observability built in. With built-in vector indexing (e.g., HNSW), metadata filtering, and powerful query semantics, ZeusDB enables similarity search, hybrid retrieval, filtering, and rapid application iteration. -
22
SAP IQ
SAP
Enhance in-the-moment decision-making with SAP IQ, our columnar relational database management system (RDBMS) optimized for Big Data analytics. Gain maximum speed, power, and security, while supporting extreme-scale enterprise data warehousing and Big Data analytics, with this affordable, efficient relational database management system (RDBMS) for SAP Business Technology Platform. Deploy as a fully managed cloud service on a major hyper scale platform. Ingest, store, and query large data volumes within a relational data lake that provides a native object storage for most file types. Provide a compatible, fully managed cloud option for SAP IQ customers that extend existing Sybase investments. Simplify the migration of existing SAP IQ databases to the cloud. Make Big Data available faster to applications and people for in-the-moment decisions. -
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Fujitsu Enterprise Postgres
Fujitsu
Fujitsu Enterprise Postgres is an exceptionally reliable and robust relational database, created for organizations that require strong query performance and high availability. It is based on the world-renowned open-source system — PostgreSQL, with additional enterprise-grade features for enhanced security and better performance. Fujitsu Enterprise Postgres is installed and operated by Fujitsu’s database experts who can also assist with the migration of data from your existing database. Based on PostgreSQL, FEP is highly compatible with other systems and applications. The simple, clean graphic user interface improves the experience for DBAs executing core database functions, such as running queries, scanning, and back-up, making your data and reporting more accessible. -
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RediSearch
Redis
Redis Enterprise includes a powerful real-time indexing, querying, and full-text search engine available on-premises and as a managed service in the cloud. Redis real-time search supports fast indexing and ingestion. It’s engineered for performance using in-memory data structures implemented in C. Scale out and partition indexes over several shards and nodes for greater speed and memory capacity. Enjoy continued operations in any scenario with five-nines availability and Active-Active failover. Redis Enterprise real-time search allows you to quickly create primary and secondary indexes on Hash and JSON datasets using an incremental indexing approach for fast index creation and deletion. The indexes let you query data at top speed, perform complex aggregations, filter by properties, numeric ranges as well as geographical distance. -
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GeoSpock
GeoSpock
GeoSpock enables data fusion for the connected world with GeoSpock DB – the space-time analytics database. GeoSpock DB is a unique, cloud-native database optimised for querying for real-world use cases, able to fuse multiple sources of Internet of Things (IoT) data together to unlock its full value, whilst simultaneously reducing complexity and cost. GeoSpock DB enables efficient storage, data fusion, and rapid programmatic access to data, and allows you to run ANSI SQL queries and connect to analytics tools via JDBC/ODBC connectors. Users are able to perform analysis and share insights using familiar toolsets, with support for common BI tools (such as Tableau™, Amazon QuickSight™, and Microsoft Power BI™), and Data Science and Machine Learning environments (including Python Notebooks and Apache Spark). The database can also be integrated with internal applications and web services – with compatibility for open-source and visualisation libraries such as Kepler and Cesium.js. -
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Vitess
Vitess
A database clustering system for horizontal scaling of MySQL. Vitess combines many important MySQL features with the scalability of a NoSQL database. Its built-in sharding features let you grow your database without adding sharding logic to your application. Vitess automatically rewrites queries that hurt database performance. It also uses caching mechanisms to mediate queries and prevent duplicate queries from simultaneously reaching your database. Vitess automatically handles functions like master failovers and backups. It uses a lock server to track and administer servers, letting your application be blissfully ignorant of database topology. Vitess eliminates the high-memory overhead of MySQL connections. Vitess servers easily handle thousands of connections at once. MySQL doesn’t natively support sharding, but you will likely need it as your database grows. -
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RushDB
RushDB
RushDB is an open-source zero-configuration graph database that instantly transforms JSON and CSV into a fully normalized, queryable Neo4j graph - without the overhead of schema design, migrations, or manual indexing. Designed for modern applications, AI, and ML workflows, RushDB provides a frictionless developer experience, combining the flexibility of NoSQL with the structured power of relational databases. With automatic data normalization, ACID compliance, and a powerful API, RushDB eliminates the complexities of data ingestion, relationship management, and query optimization - so you can focus on building, not database administration. Key Features: 1. Zero Configuration, Instant Data Ingestion 2. Graph-Powered Storage & Queries 3. ACID Transactions & Schema Evolution 4. Developer-Centric API: Query Like an SDK 5. High-Performance Search & Analytics 6. Self-Hosted or Cloud-ReadyStarting Price: $9/month -
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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. -
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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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FlySpeed SQL Query
ActiveDBSoft
The visual query designer lets you create new SQL queries by drag'n'drop, and represent off-the-shelf queries visually. It makes SQL query analysis, creation, and modification much simpler. Using FlySpeed SQL Query, you can build parameterized queries, and browse data from linked tables via foreign keys. Your queries will be saved along with the database connection right beside the database object tree, so you'll be able to continue your work from the point where you stopped last time. The history of SQL query execution is saved automatically; all the settings used during your last session will be restored the next time you start FlySpeed SQL Query. The special Portable version will allow you to keep your database connection settings and queries at your fingertips. Install FlySpeed SQL Query to your cloud folder, network or portable drive and get access to your data and settings from all of your workstations.Starting Price: $49 one-time payment -
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Tabular
Tabular
Tabular is an open table store from the creators of Apache Iceberg. Connect multiple computing engines and frameworks. Decrease query time and storage costs by up to 50%. Centralize enforcement of data access (RBAC) policies. Connect any query engine or framework, including Athena, BigQuery, Redshift, Snowflake, Databricks, Trino, Spark, and Python. Smart compaction, clustering, and other automated data services reduce storage costs and query times by up to 50%. Unify data access at the database or table. RBAC controls are simple to manage, consistently enforced, and easy to audit. Centralize your security down to the table. Tabular is easy to use plus it features high-powered ingestion, performance, and RBAC under the hood. Tabular gives you the flexibility to work with multiple “best of breed” compute engines based on their strengths. Assign privileges at the data warehouse database, table, or column level.Starting Price: $100 per month -
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CompareData
Zidsoft
Compare and synchronize sql data visually. CompareData allows you to visually compare and synchronize data between sql databases. Compare table, view or query data and see differences highlighted on the screen. Compare table metadata, generate sql sync script, use the command line and internal scheduling to automate comparison and data synchronization. • Compare data of table, query or group of tables. • Synchronize table data at row, table or group level. • Compare table metadata including columns, primary key, indices, foreign keys, triggers, permission and check constraints. • Compare stored procedures, functions and sequences, • Cross-dbms support with ODBC. • Compare resultsets of any size. • Native 64-bit application. • Multi-threaded, multi-core support. • Free for comparing data and metadata.Starting Price: $495 single user license -
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SpectX
SpectX
SpectX is a powerful log analyzer for incident investigation and data exploration. It does not ingest or index data but runs queries directly on log files stored in file systems or blob storage. Local log servers, cloud storage, Hadoop clusters, JDBC-databases, production servers, Elastic clusters, or anything that speaks HTTP - SpectX turns any text-based log files into structured virtual views. SpectX query language is inspired by piping in Unix. An extensive library of built-in query functions allows analysts to compose complex queries and get advanced insights. In addition to the browser-based interface, every query can be easily executed via RESTful API, with advanced options to customize the resultset. This makes it easy to integrate SpectX with other applications in need of clean and structured data. SpectX easy-to-read pattern matching language can flexibly match any data, no need to read or write regex.Starting Price: $79/month -
34
Outerbase
Outerbase
The interface for your database. View, update, and visualize your data collaboratively, without needing to be a database expert. No one team should have all that power. Queries, columns, rows, tables, and schemas without writing SQL. Edit your data in-line and collaboratively like you would a spreadsheet. Ditch the random snippets and notes with blocks of SQL queries, organize them here. Share your queries with the rest of the team so they’re not stuck recreating the wheel. The easiest way to query your data without ever writing a single line of SQL. Outerbase connects to the most popular databases. Select your schemas, tables, columns, and more quickly. Reduce context-switching and do it all in our intuitive user interface. Simple experiences for complex data like JSON, timestamps, and ENUMs. Embed variables to create powerful and flexible queries. Create stunning dashboards in a couple of clicks.Starting Price: $50 per month -
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Apache Doris
The Apache Software Foundation
Apache Doris is a modern data warehouse for real-time analytics. It delivers lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within a second. Storage engine with real-time upsert, append and pre-aggregation. Optimize for high-concurrency and high-throughput queries with columnar storage engine, MPP architecture, cost based query optimizer, vectorized execution engine. Federated querying of data lakes such as Hive, Iceberg and Hudi, and databases such as MySQL and PostgreSQL. Compound data types such as Array, Map and JSON. Variant data type to support auto data type inference of JSON data. NGram bloomfilter and inverted index for text searches. Distributed design for linear scalability. Workload isolation and tiered storage for efficient resource management. Supports shared-nothing clusters as well as separation of storage and compute.Starting Price: Free -
36
python-sql
Python Software Foundation
python-sql is a library to write SQL queries in a pythonic way. Simple selects, select with where condition. Select with join or select with multiple joins. Select with group_by and select with output name. Select with order_by, or select with sub-select. Select on other schema and insert query with default values. Insert query with values, and insert query with query. Update query with values. Update query with where condition. Update query with from the list. Delete query with where condition, and delete query with sub-query. Provides limit style, qmark style, and numeric style.Starting Price: Free -
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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. -
38
CrateDB
CrateDB
The enterprise database for time series, documents, and vectors. Store any type of data and combine the simplicity of SQL with the scalability of NoSQL. CrateDB is an open source distributed database running queries in milliseconds, whatever the complexity, volume and velocity of data. -
39
Alibaba Cloud DRDS
Alibaba
Distributed Relational Database Service (DRDS) is a lightweight, flexible, stable, and efficient middleware product developed by Alibaba Cloud. DRDS focuses on expanding standalone relational databases, and has been tested by core transaction links in Tmall, such as during the Singles’ Day Shopping Festival. DRDS has been used for ten years and is a trusted database service provider. Supports cluster-based data read and write and data storage. DRDS operates on multiple standalone servers, and performance is not affected by the number of user connections. Supports upgraded and downgraded data configurations, and the visualized scale-up and scale-out of data storage. Provides read and write splitting to linearly improve the reading performance. Supports multiple data splitting methods based on data types, such as parallel data splitting. Focuses on the primary shards of the database and supports parallel query execution. -
40
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 -
41
Google Cloud Datalab
Google
An easy-to-use interactive tool for data exploration, analysis, visualization, and machine learning. Cloud Datalab is a powerful interactive tool created to explore, analyze, transform, and visualize data and build machine learning models on Google Cloud Platform. It runs on Compute Engine and connects to multiple cloud services easily so you can focus on your data science tasks. Cloud Datalab is built on Jupyter (formerly IPython), which boasts a thriving ecosystem of modules and a robust knowledge base. Cloud Datalab enables analysis of your data on BigQuery, AI Platform, Compute Engine, and Cloud Storage using Python, SQL, and JavaScript (for BigQuery user-defined functions). Whether you're analyzing megabytes or terabytes, Cloud Datalab has you covered. Query terabytes of data in BigQuery, run local analysis on sampled data, and run training jobs on terabytes of data in AI Platform seamlessly. -
42
OpenObserve
OpenObserve
OpenObserve is an open source observability platform for logs, metrics, and traces that emphasizes high performance, scalability, and dramatically lower cost. It supports petabyte-scale observability thanks to features like data compression using columnar storage and the ability to use “bring your own bucket” storage (local disk, S3, GCS, Azure Blob, etc.). It is written in Rust, uses the DataFusion query engine to directly query Parquet files, and provides a stateless, horizontally scalable architecture with caching (both result and disk) to maintain speed under heavy load. It embraces open standards (OpenTelemetry compatibility, vendor-neutral APIs), so it fits into existing monitoring/logging workflows. Key modules include logs, metrics, traces, frontend monitoring, pipelines, alerts, and dashboards/visualizations.Starting Price: $0.30 per GB -
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Upsolver
Upsolver
Upsolver makes it incredibly simple to build a governed data lake and to manage, integrate and prepare streaming data for analysis. Define pipelines using only SQL on auto-generated schema-on-read. Easy visual IDE to accelerate building pipelines. Add Upserts and Deletes to data lake tables. Blend streaming and large-scale batch data. Automated schema evolution and reprocessing from previous state. Automatic orchestration of pipelines (no DAGs). Fully-managed execution at scale. Strong consistency guarantee over object storage. Near-zero maintenance overhead for analytics-ready data. Built-in hygiene for data lake tables including columnar formats, partitioning, compaction and vacuuming. 100,000 events per second (billions daily) at low cost. Continuous lock-free compaction to avoid “small files” problem. Parquet-based tables for fast queries. -
44
Back4app
Back4app
Store and query relational data on the cloud. Make it accessible over GraphQL and REST with a scalable, open-source backend. Store and query relational data through GraphQL, REST, or Parse SDKs. Add business logic using cloud functions. Make apps faster without managing infrastructure. Build relational data models in minutes, and perform complex relational queries in a truly serverless platform. Our engineer team is ready to guide you on each step of the process. From database to cloud functions we help you to migrate in the smoothest way. Keep costs in check even when you scale your apps with affordable, predictable pricing. Scaling happens automatically and, we guide the process to ensure that nothing goes wrong. Build your app exactly the way you'd like, without getting bogged down in the backend. Of course, you do. Keeping data safe is more important than ever.Starting Price: $4.99 per month -
45
Apache Drill
The Apache Software Foundation
Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage -
46
tap
Digital Society
Turn spreadsheets and data files into production-ready APIs without writing backend code. Upload CSV, JSONL, Parquet and other formats, clean and join them with familiar SQL, and expose secure, documented endpoints instantly. Built-in features include auto-generated OpenAPI docs, API key security, geospatial filters with H3 indexing, usage monitoring, and high-performance queries. You can also download transformed datasets anytime to avoid vendor lock-in. Works for single files, combined datasets, or public data portals with minimal setup. Key features - Create secure, documented APIs directly from CSV, JSONL, and Parquet. - Run familiar SQL queries to clean, join, and enrich data. - No backend setup or servers to configure or maintain. - Auto-generated OpenAPI documentation for every endpoint you create. - Secure endpoints with API keys and isolated storage for safety. - Geospatial filters, H3 indexing, and fast, optimised queries at scale.Starting Price: $10/month -
47
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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AD Query
SysOp Tools
Completely free utility for Active Directory. Lookup a user or computer and view converted schema attributes that are normally not readable. A very handy tool for schema data lookup and comparison. No installer, just run the exe. 100% free utility for use in Active Directory domains. Search individual domain users and computer objects. View object Schema & LDAP data in one simple window. View binary Schema data in “human-readable” format. Easy lookup of email aliases, last login date, etc. Export search results to XML file, open with Excel. Small program size, super quick install. AD query software for user accounts is a great time-saving utility for the busy admin! AD Query is a free utility that allows quick and easy auditing of any user or computer object within Active Directory. Unlike the standard Users and Computers MMC, AD Query shows all data populated schema, LDAP and Exchange mail-enabled attributes for the user or computer object.Starting Price: Free -
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Microsoft Power Query
Microsoft
Power Query is the easiest way to connect, extract, transform and load data from a wide range of sources. Power Query is a data transformation and data preparation engine. Power Query comes with a graphical interface for getting data from sources and a Power Query Editor for applying transformations. Because the engine is available in many products and services, the destination where the data will be stored depends on where Power Query was used. Using Power Query, you can perform the extract, transform, and load (ETL) processing of data. Microsoft’s Data Connectivity and Data Preparation technology that lets you seamlessly access data stored in hundreds of sources and reshape it to fit your needs—all with an easy to use, engaging, no-code experience. Power Query supports hundreds of data sources with built-in connectors, generic interfaces (such as REST APIs, ODBC, OLE, DB and OData) and the Power Query SDK to build your own connectors. -
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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.
