DuckDB Alternatives

LanceDB is a developer-friendly, open source database for AI. From hyperscalable vector search and advanced retrieval for RAG to streaming training data and interactive exploration of large-scale AI datasets, LanceDB is the best foundation for your AI application. Installs in seconds and fits seamlessly into your existing data and AI toolchain. An embedded database (think SQLite or DuckDB) with native object storage integration, LanceDB can be deployed anywhere and easily scales to zero when not in use. From rapid prototyping to hyper-scale production, LanceDB delivers blazing-fast performance for search, analytics, and training for multimodal AI data. Leading AI companies have indexed billions of vectors and petabytes of text, images, and videos, at a fraction of the cost of other vector databases. More than just embedding. Filter, select, and stream training data directly from object storage to keep GPU utilization high.

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.

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.

At Vaex.io we aim to democratize big data and make it available to anyone, on any machine, at any scale. Cut development time by 80%, your prototype is your solution. Create automatic pipelines for any model. Empower your data scientists. Turn any laptop into a big data powerhouse, no clusters, no engineers. We provide reliable and fast data driven solutions. With our state-of-the-art technology we build and deploy machine learning models faster than anyone on the market. Turn your data scientist into big data engineers. We provide comprehensive training of your employees, enabling you to take full advantage of our technology. Combines memory mapping, a sophisticated expression system, and fast out-of-core algorithms. Efficiently visualize and explore big datasets, and build machine learning models on a single machine.

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

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.

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.

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.

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...

ClickHouse is a fast open-source OLAP database management system. It is column-oriented and allows to generate analytical reports using SQL queries in real-time. ClickHouse's performance exceeds comparable column-oriented database management systems currently available on the market. It processes hundreds of millions to more than a billion rows and tens of gigabytes of data per single server per second. ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency. ClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure.

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.

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.

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.

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.

ParadeDB brings column-oriented storage and vectorized query execution to Postgres tables. Users can choose between row and column-oriented storage at table creation time. Column-oriented tables are stored as Parquet files and are managed by Delta Lake. Search by keyword with BM25 scoring, configurable tokenizers, and multi-language support. Search by semantic meaning with support for sparse and dense vectors. Surface results with higher accuracy by combining the strengths of full text and similarity search. ParadeDB is ACID-compliant with concurrency controls across all transactions. ParadeDB integrates with the Postgres ecosystem, including clients, extensions, and libraries.

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.

Your cloud data platform. Secure and easy access to any data with infinite scalability. Get all the insights from all your data by all your users, with the instant and near-infinite performance, concurrency and scale your organization requires. Seamlessly share and consume shared data to collaborate across your organization, and beyond, to solve your toughest business problems in real time. Boost the productivity of your data professionals and shorten your time to value in order to deliver modern and integrated data solutions swiftly from anywhere in your organization. Whether you’re moving data into Snowflake or extracting insight out of Snowflake, our technology partners and system integrators will help you deploy Snowflake for your success.

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.

KS DB Merge Tools is an easy to use diff & merge tool for MySQL, MariaDB, Oracle Database, SQL Server, PostgreSQL, SQLite, MS Access and Cross-DBMS databases allowing to compare and sync both schema and data. Starting with a schema changes summary, results can be narrowed down to object lists of particular object type (table definitions, views, etc.), and then down to definition of particular object. Data changes can be retrieved as a high-level list of changes totals across all tables in the database, each total row count can be observed as a side-by-side list of rows for the given table, each changed row can be analyzed for changes in each column. Various diff results provide quick filters to show only new/changed/new+changed items (schema objects or table data rows), ability to select required changed items and generate scripts to apply these changes to the other side database. This script can be executed immediately or saved for future use.

Database X-Ray is a must-have SQL Server utility that allows the viewing of all database objects in a tabular format, and shows relationships between each object, including objects referenced by a given object, as well as objects that reference that object. This includes Tables, Views, Stored Procedures, Functions, and Triggers, allowing you to see at a glance what will be affected by deleting or changing an object in your database. (You won't get that from a database diagram!) In addition, you can view the DDL (Data Definition Language) or code that created each object, copy it to the clipboard, and use it in any way you like. All you need to get started is a valid connection string to a database that can be accessed from wherever you install Database X-Ray, whether local or remote. Works with Azure SQL Database too!

Only search engine software available with the fully integrated structure of an SQL relational database (RDBMS). SQL offers versatility as the application development model and numerous advantages for addressing complicated search requirements. Flexibility to implement unanticipated new search functionality as the need arises. 250,000-word vocabulary and phrase concept associations for natural language queries. Store and search text documents of unlimited size within standard database tables. Solves the difficult challenge of integrating text search with an RDBMS. Can be customized to be used as a content management, e-commerce, portal or knowledge management system. Can handle wildcards and phrases. Easy to administer. Texis is the core technology for all Thunderstone products. It is the only search engine software available with the fully integrated structure of an SQL relational database (RDBMS) that intelligently queries and manages databases containing natural language text.

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.

Nucleon Database Master is a modern, powerful, intuitive and easy to use database query, administration, and management software with a consistent and modern user interface. Database Master simplifies managing, monitoring, querying, editing, visualizing, designing relational and NoSQL DBMS. Database Master allows you to execute extended SQL, JQL and C# (Linq) query scripts, provides all database objects such as tables, views, procedures, packages, columns, indexes, relationships (constraints), collections, triggers and other database objects.

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.

One area hasn’t benefited from the DevOps movement as much: The database change process. It’s time to bring CI/CD to the database. Application release technology has come a long way in the past several years. It used to take weeks or even months to release new software. Now that organizations have adopted new workflows and processes, the time it takes to complete a release has been reduced to days and even hours. Database schema migrations are an essential task for every software project. There are several different reasons why updates to the database are required. New features require new attributes in existing tables or entirely new tables. Bug fixes may lead to changes in names or data types in the database. Performance issues that require additional indexes in the database. Even in organizations that have adopted DevOps, manual rework is the norm when it comes to database schema and stored procedure changes.

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.

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.

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.

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.

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.

Perhaps you want to give your clients access to their LIMS data and reports via the web. AIS labPortal allows you to do just that. Paper copies of sample analyses needn’t be sent out in the post to customers. Using their unique login and security password, clients can access data from their computer, which is not only safer and less time-consuming but also more environmentally friendly. labPortal is a web-based portal that securely stores your clients’ sample information and data in the cloud, allowing them to easily access it instantly from their own desktop, tablet or phone. The labPortal interface is 'inbox' style which is simple and easy to use with an enhanced query engine, conditional highlighting and Microsoft Excel export. The software features a simple and easy-to-use sample registration form which allows users to pre-register samples online. Transcribing data is a time-consuming and tedious activity.

Xata is a combination of a relational database, an analytics engine, and a free-text search engine. All made simple by a spreadsheet-like UI and a single powerful data API, with granular security, zero-downtime migrations, subscriptions, ACID transactions, and caching built-in. If you don’t worry about servers when deploying your application, why should you worry about servers (or nodes, or clusters) when using a database service? The simple global RESTful API for inserting, querying, aggregating, and searching makes Xata the perfect companion for Serverless and No-Code/Low-Code development platforms. Xata allows you to iteratively build your database schema as you add sample data, all via a spreadsheet-like UI. You can add new tables, columns, data, and create queries and views. It then gives you code samples ready to be used in your application. This gives you flexibility as you develop and, as the application grows, the strict schema keeps your data safe and correct.

Empress Embedded Database engine is the heartbeat of EMPRESS RDBMS, a relational database management system specializing in embedded database technology – from car navigation systems to mission critical military command and control, from Internet routers to complex medical systems, EMPRESS beats steadily, 24/7 at the core of embedded systems applications everywhere. Empress kernel level mr API is a unique feature of Empress that gives users access to the Embedded Database kernel libraries. This Empress API provides the fastest means of accessing Empress databases. MR Routines give the developer maximum control over time and space in developing real-time embedded database applications. Empress ODBC and JDBC APIs applications to access Empress databases in both standalone and client/server mode. Empress ODBC and JDBC APIs enable many 3rd party ODBC and JDBC capable software packages to access a local Empress database or via Empress Connectivity Server.

How is platform independent eXtremeDB different? - Hybrid data storage. Unlike other IMDS, eXtremeDB can be all-in-memory, all-persistent, or have a mix of in-memory tables and persistent tables - Active Replication Fabric™ is unique to eXtremeDB, offering bidirectional replication, multi-tier replication (e.g. edge-to-gateway-to-gateway-to-cloud), compression to maximize limited bandwidth networks and more - Row & Columnar Flexibility for Time Series Data supports database designs that combine row-based and column-based layouts, in order to best leverage the CPU cache speed - Embedded and Client/Server. Fast, flexible eXtremeDB is data management wherever you need it, and can be deployed as an embedded database system, and/or as a client/server database system -A hard real-time deterministic option in eXtremeDB/rt Designed for use in resource-constrained, mission-critical embedded systems. Found in everything from routers to satellites to trains to stock markets worldwide

Proactively manage all major DBMSs (SQL Server, Azure SQL Database, Oracle Database, Sybase ASE and IQ, Db2 LUW and z/OS, Redshift, MySQL, PostgreSQL, and Greenplum) from a single common interface. Reduce training requirements and streamline collaboration among different teams across the organization. Manage multiple Oracle-specific schema object types and SQL Server advanced object properties such as temporal tables, in-memory tables, and natively compiled triggers, procedures and functions. Comprehensive tools help you manage space, data and performance to keep your databases optimized and available. Manage the performance of your databases with a built-in process monitor that helps you understand who is connected to your database along with each user's current activity and session-related data. Sophisticated diagnostics help you pinpoint performance inefficiencies that result in poor space management, tracking key database metadata and performance metrics over time.

DbSchema is for visual designing the schema in a team, deploy and document the schema. Other integrated features like data explorer, visual query editor, data generator, etc., makes DbSchema an every-day tool for everybody who interacts with databases. DbSchema supports all relational and No-SQL databases, including MySQL, PostgreSQL, SQLite, Microsoft SQL Server, MongoDB, MariaDB, Redshift, Snowflake, Google and more. DbSchema is reverse-engineering the database schema from the database and visualize it as diagrams. You will interact with the database using diagrams and visual tools. DbSchema model is using its copy of schema structure, independent from the database. This allows the schema deployment on multiple databases, save the design model to file, store it in GIT and design the schema in a team, design the schema without database connectivity, compare different versions of the schema and generate SQL migration scripts.

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.

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.

It dramatically cuts the effort, cost, and risk of migrating to/from any of the following database formats: Oracle, MySQL, MariaDB, SQL Server, PostgreSQL, IBM DB2, IBM Informix, InterSystems Caché, Teradata, Visual Foxpro, SQLite, FireBird, InterBase, Microsoft Access, Microsoft Excel, Paradox, Lotus, dBase, CSV/Text and transfer any ODBC DSN data source to them. This software can help you quickly migrate a variety of data, structures and objects, saving you a lot of time and money. It will automatically migrate all table structures, data, schemas(Oracle, SQL Server 2000 or higher, PostgreSQL, IBM DB2 and so), LOBs(Large Text/Binary Objects), primary/foreign keys, indexes, auto-increment(serial), comments and default values and more. You can migrate data between two different character sets(e.g.: UTF8, CP1250 etc.) and the software automatically convert different data encodings. You can also change the field name/data type/nullable/precision/numscale or filter data when migrating.

Starburst helps you make better decisions with fast access to all your data; Without the complexity of data movement and copies. Your company has more data than ever before, but your data teams are stuck waiting to analyze it. Starburst unlocks access to data where it lives, no data movement required, giving your teams fast & accurate access to more data for analysis. Starburst Enterprise is a fully supported, production-tested and enterprise-grade distribution of open source Trino (formerly Presto® SQL). It improves performance and security while making it easy to deploy, connect, and manage your Trino environment. Through connecting to any source of data – whether it’s located on-premise, in the cloud, or across a hybrid cloud environment – Starburst lets your team use the analytics tools they already know & love while accessing data that lives anywhere.

Suneido™ is a complete, integrated application platform – a system for developing and deploying applications without the frustrations of integrating multiple different products. Suneido incorporates an object-oriented programming language, client-server relational database software, and application frameworks and components. It includes the integrated development environment (IDE) used to create applications as well as the client and server required to run applications across networks. Suneido is Open Source – it is provided free, with complete source code. Our mission is to provide a simple, open, lightweight, industrial strength alternative to large, complex, expensive, closed application technologies such as Visual Basic, Access, FoxPro, Delphi, Oracle, and SQL Server.

Here are some areas where Database Tour has competitive advantages among database tools in the marketplace. Preparing database queries in SQL editors with syntax highlighting, code completion, and Ctrl+clickable objects. Multiple windows with separate transactions. There is a possibility to execute multi-statement SQL scripts. Collecting SQL execution statistics for each query window. Performing useful operations with databases, such as searching and replacing text, batch data processing etc. Database Tour data grids give you the ability to view CLOB/MEMO (large text) and graphic data, expand rows, use autoscrolling, sorting, selecting group of records, copying data etc. Data in tables can be highlighted depending on its content (so called conditional formatting). There is a tool for working with BLOB fields, such as large text and graphics.

Create a backend in less than 2 minutes. Start your project with a Postgres database, authentication, instant APIs, real-time subscriptions and storage. Build faster and focus on your products. Every project is a full Postgres database, the world's most trusted relational database. Add user sign-ups and logins, securing your data with Row Level Security. Store, organize and serve large files. Any media, including videos and images. Write custom code and cron jobs without deploying or scaling servers. There are many example apps and starter projects to get going. We introspect your database to provide APIs instantly. Stop building repetitive CRUD endpoints and focus on your product. Type definitions built directly from your database schema. Use Supabase in the browser without a build process. Develop locally and push to production when you're ready. Manage Supabase projects from your local machine.

Firebird is a relational database offering many ANSI SQL standard features that runs on Linux, Windows, and a variety of Unix platforms. Firebird offers excellent concurrency, high performance, and powerful language support for stored procedures and triggers. It has been used in production systems, under a variety of names, since 1981. The Firebird Project is a commercially independent project of C and C++ programmers, technical advisors and supporters developing and enhancing a multi-platform relational database management system based on the source code released by Inprise Corp (now known as Borland Software Corp) on 25 July, 2000. The Firebird Project supplies users, developers, and administrators with various kinds of documentation, from Quick Start guides to expert-level articles devoted to various aspects of Firebird.

Robust apps have strong data models at their core, our AI-powered schema builder will help you nail yours from the ground up. ROQ auto-runs and deploys migrations when you modify your tables or fields, so you don't have to worry about writing migrations anymore. Multi-tenancy usually adds a dimension of complexity to every layer of code. With ROQ, you don't need to think about tenants. It just works - on your APIs, login, signup, and data access. We host highly secure login and signup forms that are visually customizable so that you can start building your app code right away. Most apps need to collect different data for each role that signs up to your app, use ROQ's Signup form variants to do just that. With our client-side libraries, you can protect a page or a component with ease.

Natively store data for graph, document and search needs. Utilize feature-rich access with one query language. Map data natively to the database and access it with the best patterns for the job – traversals, joins, search, ranking, geospatial, aggregations – you name it. Polyglot persistence without the costs. Easily design, scale and adapt your architectures to changing needs and with much less effort. Combine the flexibility of JSON with semantic search and graph technology for next generation feature extraction even for large datasets.

Accelerate, design, debug and deliver serverless faster! The most powerful collection of DynamoDB tools with single-table aware data browser, designer, provisioning planner, migration manager and metrics. Browser and manage tables that understands your single-table designs. Manage schemas and entities with the single-table designer. Determine best provisioning with real historical data. Upgrade and downgrade data with the migration manager. See exactly how your DynamoDB table is performing with detailed metrics at the account, table and single-table entity levels. Automated error detection for application, database and service events. Create Alarms and alerts for application log events, metrics, events and DynamoDB performance. Don't get swamped by alerts via smart notification dampening. Select monitored resources by tags, regular expressions or list.

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.

A Powerful MySQL Development and Administration Solution. SQLyog Ultimate enables database developers, administrators, and architects to visually compare, optimize, and document schemas. SQLyog Ultimate includes a power tool to automate and schedule the synchronization of data between two MySQL hosts. Create the job definition file using the interactive wizard. The tool does not require any installation on the MySQL hosts. You can use any host to run the tool. SQLyog Ultimate includes a power tool to interactively synchronize data. Run the tool in attended mode to compare data from source and target before taking action. Using the intuitive display, compare data on source and target for every row to decide whether it should be synchronized in which direction. SQLyog Ultimate includes a power tool to interactively compare and synchronize schema. View the differences between tables, indexes, columns, and routines of two databases.

TEXTML Server is a database system designed to efficiently store and retrieve XML documents as well as documents in any format (PDF files, image files, etc.). TEXTML Server is a building block for applications that need to manage large amounts of XML information or for any application containing loosely structured information that cannot be efficiently handled by traditional relational database systems. The fact that it is designed with XML at its core makes TEXTML Server extremely versatile and ideally suited to a wide variety of applications. It can be used on its own or in tandem with traditional relational databases. It supports two-tier and n-tier architectures, including browser-based applications. Your client application (or the tier of your application that includes calls to TEXTML SDK) can run on Windows and many flavors of Linux. See the TEXTML Server Installation Guide for full information on system requirements.