Best Data Management Software for SQL - Page 4

Compare the Top Data Management Software that integrates with SQL as of July 2025 - Page 4

This a list of Data Management software that integrates with SQL. Use the filters on the left to add additional filters for products that have integrations with SQL. View the products that work with SQL in the table below.

  • 1
    Zerve AI

    Zerve AI

    Zerve AI

    Merging the best of a notebook and an IDE into one integrated coding environment, experts can explore their data and write stable code at the same time with fully automated cloud infrastructure. Zerve’s data science development environment gives data science and ML teams a unified space to explore, collaborate, build, and deploy data science & AI projects like never before. Zerve offers true language interoperability, meaning that as well as being able to use Python, R, SQL, or Markdown all in the same canvas, users can connect these code blocks to each other. No more long-running code blocks or containers, with Zerve enjoying unlimited parallelization at any stage of the development journey. Analysis artifacts are automatically serialized, versioned, stored, and preserved for later use, meaning easily changing a step in the data flow without needing to rerun any preceding steps. Fine-grained selection of compute resources and extra memory for complex data transformation.
  • 2
    DataLang

    DataLang

    DataLang

    Connect your data sources, configure some data views (i.e. SQL scripts), configure a GPT Wizard, create a custom GPT, and share it with your users, employees, or clients. Expose a specific set of data (using SQL) to train GPT, and then chat with it in natural language. Data insights just got a whole lot easier, you can follow simple steps and let DataLang do the heavy lifting. Configure your connection string and give it a name. Use SQL to train GPT with your own data rows, select the data sources to train GPT with, and leverage GPT to talk to your data in real time. Create custom GPT Assistants to chat with your data. Configure a GPT to share it with your users, or customers. Your connection string credentials are securely encrypted in our system and only decrypted when necessary for data operations. We are committed to the security and confidentiality of your information. You can ask DataLang almost any question you would ask a data analyst.
    Starting Price: $19 per month
  • 3
    Onehouse

    Onehouse

    Onehouse

    The only fully managed cloud data lakehouse designed to ingest from all your data sources in minutes and support all your query engines at scale, for a fraction of the cost. Ingest from databases and event streams at TB-scale in near real-time, with the simplicity of fully managed pipelines. Query your data with any engine, and support all your use cases including BI, real-time analytics, and AI/ML. Cut your costs by 50% or more compared to cloud data warehouses and ETL tools with simple usage-based pricing. Deploy in minutes without engineering overhead with a fully managed, highly optimized cloud service. Unify your data in a single source of truth and eliminate the need to copy data across data warehouses and lakes. Use the right table format for the job, with omnidirectional interoperability between Apache Hudi, Apache Iceberg, and Delta Lake. Quickly configure managed pipelines for database CDC and streaming ingestion.
  • 4
    Tarantool

    Tarantool

    Tarantool

    Corporations need a way to ensure uninterrupted operation of their systems, high speed of data processing, and reliability of storage. The in-memory technologies have proven themselves well in solving these problems. For more than 10 years, Tarantool has been helping companies all over the world build smart caches, data marts, and golden client profiles while saving server capacity. Reduce the cost of storing credentials compared to siloed solutions and improve the service and security of client applications. Reduce data management costs of maintaining a large number of disparate systems that store customer identities. Increase sales by improving the speed and quality of customer recommendations for goods or services through the analysis of user behavior and user data. Improve mobile and web channel service by accelerating frontends to reduce user outflow. IT systems of large organizations operate in a closed loop of a local network, where data circulates unprotected.
  • 5
    Mimer SQL
    The Mimer SQL codebase is the most modern in the world. It is modular, extremely maintainable, easily expandable, and designed with portability in mind. We know how to squeeze out the best from computers and operating systems, and so does Mimer SQL. Our brand new SQL compiler with the latest in optimization techniques, coupled with a world-class storage engine and no limits besides what the hardware imposes, lays the groundwork for speed and efficiency that is second to none. Continuously improved and refined, the security features of Mimer SQL leave nothing wanting. Data in use, data in motion, and data at rest are all covered with time-tested, reliable, and documented algorithms. Mimer SQL is the ideal companion for the modern in-vehicle computation solution. Its performance and reliability match the hard demands of secure, flexible, and reliable data management in today’s autonomous and connected cars.
  • 6
    ITTIA DB
    The ITTIA DB product family combines the best of time series, real-time data streaming, and analytics for embedded systems to reduce development time and costs. ITTIA DB IoT is a small-footprint embedded database for real-time resource-constrained 32-bit microcontrollers (MCUs), and ITTIA DB SQL is a high-performance time-series embedded database for single or multicore microprocessors (MPUs). Both ITTIA DB products enable devices to monitor, process, and store real-time data. ITTIA DB products are also built for the automotive industry Electronic Control Units (ECUs). ITTIA DB data security protocols offer data protection against malicious access with encryption, authentication, and DB SEAL. ITTIA SDL is conformant to the principles of IEC/ISO 62443. Embed ITTIA DB to collect, process, and enrich incoming real-time data streams in a purpose-built SDK for edge devices. Search, filter, join, and aggregate at the edge.
  • 7
    Google Cloud Datastream
    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.
  • 8
    XTDB

    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.
  • 9
    kdb Insights
    kdb Insights is a cloud-native, high-performance analytics platform designed for real-time analysis of both streaming and historical data. It enables intelligent decision-making regardless of data volume or velocity, offering unmatched price and performance, and delivering analytics up to 100 times faster at 10% of the cost compared to other solutions. The platform supports interactive data visualization through real-time dashboards, facilitating instantaneous insights and decision-making. It also integrates machine learning models to predict, cluster, detect patterns, and score structured data, enhancing AI capabilities on time-series datasets. With supreme scalability, kdb Insights handles extensive real-time and historical data, proven at volumes of up to 110 terabytes per day. Its quick setup and simple data intake accelerate time-to-value, while native support for q, SQL, and Python, along with compatibility with other languages via RESTful APIs.
  • 10
    SQL Connect

    SQL Connect

    SQL Connect

    SQL Connect is a desktop-based SQL development tool designed for Oracle Cloud applications, offering a comprehensive suite of features for efficient data querying and management. It provides real-time access to Oracle ERP, SCM, and HCM Pods, enabling users to execute ad-hoc SQL queries, browse database objects, and export results to CSV or Excel formats. It supports background query execution, allowing long-running queries to be processed without interrupting the user's workflow. Additionally, SQL Connect includes IntelliSense for code completion, a SQL Minimap for script navigation, and Git integration for version control and collaborative development. It is secured by Oracle Cloud Role access. It caters to individual users, contractors, developers, consultants, and Oracle Cloud experts seeking a robust SQL IDE for Oracle Cloud environments.
  • 11
    CloudBeaver Enterprise
    CloudBeaver Enterprise is a lightweight, browser-based data management platform designed for secure, multi-source database operations. It enables seamless integration with SQL, NoSQL, and cloud databases, including AWS, Microsoft Azure, and Google Cloud Platform (GCP), through its cloud explorer feature. It supports a range of functionalities such as data visualization, SQL script execution with smart autocompletion, entity-relationship diagramming, and AI-assisted query generation. Deployment is simplified via a single Docker command, and the system supports offline server installations without requiring internet access. Advanced user management capabilities include integration with enterprise authentication systems like AWS SSO, SAML, and OpenID, allowing for secure access control and user provisioning. CloudBeaver Enterprise also facilitates collaboration among teams by enabling shared access to resources and connections.
  • 12
    Oracle Real Application Clusters (RAC)
    Oracle Real Application Clusters (RAC) is a unique, scale-everything, highly available database architecture that transparently scales both reads and writes for all workloads, including OLTP, analytics, AI vectors, SaaS, JSON, batch, text, graph, IoT, and in-memory. It effortlessly scales complex applications such as SAP, Oracle Fusion Applications, and Salesforce workloads. Oracle RAC delivers the lowest latency and highest throughput for all data needs through its unique fused cache across servers, ensuring ultrafast local data access. Parallelized workloads across all CPUs guarantee maximum throughput, and the integration of Oracle’s storage design enables seamless online storage expansion. Unlike other databases that depend on public cloud infrastructures, sharding, or read replicas for scalability, Oracle RAC guarantees the lowest latency and highest throughput out of the box.
  • 13
    Databricks Data Intelligence Platform
    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.
  • 14
    Qubole

    Qubole

    Qubole

    Qubole is a simple, open, and secure Data Lake Platform for machine learning, streaming, and ad-hoc analytics. Our platform provides end-to-end services that reduce the time and effort required to run Data pipelines, Streaming Analytics, and Machine Learning workloads on any cloud. No other platform offers the openness and data workload flexibility of Qubole while lowering cloud data lake costs by over 50 percent. Qubole delivers faster access to petabytes of secure, reliable and trusted datasets of structured and unstructured data for Analytics and Machine Learning. Users conduct ETL, analytics, and AI/ML workloads efficiently in end-to-end fashion across best-of-breed open source engines, multiple formats, libraries, and languages adapted to data volume, variety, SLAs and organizational policies.
  • 15
    QuasarDB

    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.
  • 16
    Apache Drill

    Apache Drill

    The Apache Software Foundation

    Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage
  • 17
    Presto

    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.
  • 18
    Apache Spark

    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.
  • 19
    DuckDB

    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.
  • 20
    ksqlDB

    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.
  • 21
    Feast

    Feast

    Tecton

    Make your offline data available for real-time predictions without having to build custom pipelines. Ensure data consistency between offline training and online inference, eliminating train-serve skew. Standardize data engineering workflows under one consistent framework. Teams use Feast as the foundation of their internal ML platforms. Feast doesn’t require the deployment and management of dedicated infrastructure. Instead, it reuses existing infrastructure and spins up new resources when needed. You are not looking for a managed solution and are willing to manage and maintain your own implementation. You have engineers that are able to support the implementation and management of Feast. You want to run pipelines that transform raw data into features in a separate system and integrate with it. You have unique requirements and want to build on top of an open source solution.
  • 22
    Zepl

    Zepl

    Zepl

    Sync, search and manage all the work across your data science team. Zepl’s powerful search lets you discover and reuse models and code. Use Zepl’s enterprise collaboration platform to query data from Snowflake, Athena or Redshift and build your models in Python. Use pivoting and dynamic forms for enhanced interactions with your data using heatmap, radar, and Sankey charts. Zepl creates a new container every time you run your notebook, providing you with the same image each time you run your models. Invite team members to join a shared space and work together in real time or simply leave their comments on a notebook. Use fine-grained access controls to share your work. Allow others have read, edit, and run access as well as enable collaboration and distribution. All notebooks are auto-saved and versioned. You can name, manage and roll back all versions through an easy-to-use interface, and export seamlessly into Github.
  • 23
    AI2sql

    AI2sql

    AI2sql.io

    With AI2sql, engineers and non-engineers can easily write efficient, error-free SQL queries without knowing SQL. All you need to do is enter a few keywords about your data - AI2sql automatically builds an optimized SQL query for your data resulting in extremely fast performance. We wanted to share some exciting numbers with you about how many people have tried out AI2sql, and what they've been able to accomplish with it. To get the best results with AI2sql, it is important to clearly define your goals and use the tool's customization options, test and verify the generated SQL. You can also try changing the prompts or input used to generate the SQL statements to see if this results in more accurate or efficient queries.
  • 24
    Savant

    Savant

    Savant

    Automate data access from data platforms and apps, explore, prep, blend, analyze and deliver bot-driven insights where and when needed. From data access to delivery of insights, create workflows in minutes to automate every step of analytics from data access to delivery of insights. Put an end to shadow analytics. Create and collaborate with all stakeholders in one platform. Audit and govern workflows. The single platform for supply-chain, HR, sales & marketing analytics integrating Fivetran, Snowflake, DBT, Workday, Pendo, Marketo, PowerBI. No code. No limits. Savant's no-code platform lets you stitch, transform and analyze data using the same functions you're comfortable using in Excel and SQL. All steps are automatable, so you can focus on analysis, not tedious manual work.
  • 25
    AI Query

    AI Query

    AI Query

    Use simple English and let AI do the heavy lifting for you. With AI Query anyone can create efficient SQL queries, without even knowing a thing about it. Once your database schema is ready, you can easily generate SQL queries with simple text prompts. Let the AI do the work for you.
    Starting Price: $10 per month
  • 26
    Quadratic

    Quadratic

    Quadratic

    Quadratic enables your team to work together on data analysis to deliver faster results. You already know how to use a spreadsheet, but you’ve never had this much power. Quadratic speaks Formulas and Python (SQL & JavaScript coming soon). Use the language you and your team already know. Single-line formulas are hard to read. In Quadratic you can expand your recipes to as many lines as you need. Quadratic has Python library support built-in. Bring the latest open-source tools directly to your spreadsheet. The last line of code is returned to the spreadsheet. Raw values, 1/2D arrays, and Pandas DataFrames are supported by default. Pull or fetch data from an external API, and it updates automatically in Quadratic's cells. Navigate with ease, zoom out for the big picture, and zoom in to focus on the details. Arrange and navigate your data how it makes sense in your head, not how a tool forces you to do it.
  • 27
    SQLGPT

    SQLGPT

    SQLGPT

    Import your database schema and easily generate customized queries. Using ChatGPT to write and understand your SQL requests. To export only the schema (i.e., the database structure) in a MySQL database, you can use the mysqldump command with the no-data option. Our platform is designed to connect to your existing database and provide you with tools to manage and analyze your data. We understand that the security and privacy of your data are of utmost importance, and we take all necessary precautions to ensure that your data remains secure and confidential. When you use our platform, your data remains under your control and stored in your own database. We do not collect, store, or share your data with any third-party entities. Select the database you want to export. You can download the exported file to your computer or save it to the selected location. You can save it to your computer or send it to a remote server.
  • 28
    LlamaIndex

    LlamaIndex

    LlamaIndex

    LlamaIndex is a “data framework” to help you build LLM apps. Connect semi-structured data from API's like Slack, Salesforce, Notion, etc. LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models. LlamaIndex provides the key tools to augment your LLM applications with data. Connect your existing data sources and data formats (API's, PDF's, documents, SQL, etc.) to use with a large language model application. Store and index your data for different use cases. Integrate with downstream vector store and database providers. LlamaIndex provides a query interface that accepts any input prompt over your data and returns a knowledge-augmented response. Connect unstructured sources such as documents, raw text files, PDF's, videos, images, etc. Easily integrate structured data sources from Excel, SQL, etc. Provides ways to structure your data (indices, graphs) so that this data can be easily used with LLMs.
  • 29
    Polars

    Polars

    Polars

    Knowing of data wrangling habits, Polars exposes a complete Python API, including the full set of features to manipulate DataFrames using an expression language that will empower you to create readable and performant code. Polars is written in Rust, uncompromising in its choices to provide a feature-complete DataFrame API to the Rust ecosystem. Use it as a DataFrame library or as a query engine backend for your data models.
  • 30
    Baidu Palo

    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.