Open Source Windows Database Software - Page 19
Sort By:
Database Software for Windows
View 204 business solutions-
Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
-
Veeam Data Platform v13.1 - Get Your Free TrialTry Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
-
1
Speedment
Speedment is a Stream ORM Java Toolkit and Runtime
Speedment is an open-source Java Stream ORM toolkit and runtime. The toolkit analyzes the metadata of an existing SQL database and automatically creates a Java representation of the data model. This powerful ORM enables you to create scalable and efficient Java applications using standard Java streams with no need to type SQL or use any new API. Speedment was originally developed by researchers and engineers based in Palo Alto with the purpose to simplify and streamline the development of Java database applications by leveraging the Java Stream API. Speedment is licensed under the business-friendly Apache 2 license. Contribution from users is encouraged. Please feel free to request new features, suggest improvements and file bug reports. Assuming you have Maven installed and a relational database available, you can start using Speedment in a minute. Automatic Java representation of the latest state of your database eliminates boilerplate code and the need of manually writing Java. -
2
Spring Data Neo4j
Provide support to increase developer productivity in Java
Spring Data Neo4j, part of the larger Spring Data family, provides easy configuration and access to Neo4j Graph Databases from Spring applications. It offers three different levels of abstraction to access the store. The Neo4j client, the Neo4j Template, and the Neo4j Repositories. Spring Data Neo4j offers advanced features to map annotated entity classes to the Neo4j Graph Database. The template programming model is equivalent to other Spring templates and builds the basis for interaction with the graph and is also used for the Spring Data repository support. Spring Data Neo4j is a core part of the Spring Data project which aims to provide convenient data access for NoSQL databases. Spring Data builds on Spring Framework, check the spring.io web-site for a wealth of reference documentation. If you are just starting out with Spring, try one of the guides. -
3
SpringBlade
Microservice architecture that provides SpringCloud solutions
BladeX is a well-designed microservice architecture that provides a full set of SpringCloud solutions. Open source China's first batch of microservice architectures that perfectly integrate SpringCloud Alibaba series components are upgraded and optimized based on stable production commercial projects, and are closer to enterprise-level needs. Pursuing enterprise development More efficient, easier to deploy, and more stable. The multi-tenant architecture that meets the Chinese-style needs supports flexible combinations of multiple modes such as multi-tenant-one database, one-tenant-one database, and multi-tenant multi-database. The system provides three configurations of menu button authority, data authority, and interface authority. The combination configuration method based on annotation + Web is flexible and takes effect immediately. Deeply customize the Flowable workflow to meet SpringCloud distributed scenarios, escort complex processes, etc. -
4
StarRocks
StarRocks is a next-gen sub-second MPP database for full analytics
StarRocks is the next generation of real-time SQL engines for enterprise analytics. Real-time analytics is notoriously difficult. Complex data pipelines and de-normalized tables have always been a necessary evil. Processing any updates or deletes once data arrives has not been possible- until now. StarRocks solves these challenges and makes real-time analytics easy. Get amazing query performance on Star or Snowflake Schemas directly. From canceled orders to updated items, your analytics applications can easily handle them with StarRocks. From streaming data to change data capture, StarRocks meets the data ingestion demands of real-time analytics. Scale storage and computing power horizontally and support tens of thousands of concurrent users. All of your BI tools work with StarRocks through standard SQL. StarRocks provides superior performance. It is also a unified OLAP covering most data analytics scenarios. -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
-
5
Starcounter
Starcounter is an in-memory database application engine
Starcounter is a fused ACID memory-centric database engine and C# VM that makes it easy to create fast line-of-business applications by merging primary and secondary memory and using server-side view-models. Applications are written in regular C#, LINQ and SQL. Even the ACID transactions are written in regular C# code. Starcounter applications let you achieve 50 to 1000 times better performance without adding complexity. Full Visual Studio support including IntelliSense, debugger and performance profiler. -
6
Stripe Sync Engine
Sync your Stripe account to you Postgres database
stripe-sync-engine is a tool by Supabase that continuously syncs Stripe data into a Postgres database using webhooks. It ensures that billing-related Stripe objects like customers, subscriptions, and invoices are always up to date in your local database. This makes it easy to run analytics, reporting, or custom business logic using SQL without hitting Stripe’s API repeatedly. -
7
Supabase JS
An isomorphic Javascript client for Supabase
supabase-js is the official JavaScript client library for interacting with Supabase services. It enables developers to easily access Supabase’s Postgres database, authentication, storage, and real-time subscriptions through a unified client. Designed for frontend and full-stack apps, supabase-js integrates smoothly with modern frameworks and supports both browser and server environments. -
8
SymmetricDS
SymmetricDS is database replication and file synchronization software
SymmetricDS is an open-source platform for database replication and synchronization across heterogeneous systems. It supports multi-master and one-way replication with conflict resolution and works over unreliable networks. SymmetricDS is ideal for distributed applications, data warehousing, and edge deployments where consistency and availability are key. -
9
Tarantool
Get your data in RAM, get compute close to data, enjoy the performance
In OLTP scenarios, Tarantool can be used instead of relational databases. Such a solution will work many times faster. With Tarantool, you can replace the traditional bundle of database & cache and reduce operational costs. Tarantool is tolerant of write-heavy loads. It also allows keeping full-featured applications close to the data, thus reducing data access network latency to zero. The open-source Community Edition lets you develop applications and speed up a system in operation. It features synchronous replication, affords easy scalability, and includes tools to develop efficient applications. The Tarantool community helps with any practical questions regarding the Community Edition. Large enterprises have demanding requirements for information safety and security. Besides modules for integrating with the company's existing technological suite, Tarantool Enterprise Edition provides tools for administration, deployment, and security management. -
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
-
10
VectorChord
Scalable, fast, and disk-friendly vector search in Postgres
VectorChord is an open-source vector database built for local and edge deployment. It supports efficient vector indexing and retrieval using ANN (approximate nearest neighbor) algorithms and is optimized for integration with LLM and AI applications. VectorChord is lightweight and can be embedded in a variety of environments for fast semantic search. -
11
Vespa
The open big data serving engine
Make AI-driven decisions using your data, in real-time. At any scale, with unbeatable performance. Vespa is a full-featured text search engine and supports both regular text search and fast approximate vector search (ANN). This makes it easy to create high-performing search applications at any scale, whether you want to use traditional techniques or a modern vector-based approach. You can even combine both approaches efficiently in the same query, something no other engine can do. Recommendation, personalization and targeting involves evaluating recommender models over content items to select the best ones. Vespa lets you build applications which does this online, typically combining fast vector search and filtering with evaluation of machine-learned models over the items. This makes it possible to make recommendations specifically for each user or situation, using completely up to date information. -
12
Vitess
Vitess is a database clustering system for horizontal scaling of MySQL
Vitess is a database clustering system for horizontal scaling of MySQL through generalized sharding. By encapsulating shard-routing logic, Vitess allows application code and database queries to remain agnostic to the distribution of data onto multiple shards. With Vitess, you can even split and merge shards as your needs grow, with an atomic cutover step that takes only a few seconds. Vitess has been a core component of YouTube's database infrastructure since 2011, and has grown to encompass tens of thousands of MySQL nodes. -
13
Voldemort
A distributed key-value storage system
Voldemort is a distributed database that’s an open source clone of Amazon’s Dynamo. It automatically replicates data over multiple servers, and automatically partitions them as well so each server only contains a subset of the total data. It offers many other features such as pluggable serialization support, data item versioning and an SSD Optimized Read Write storage engine. Voldemort is not a relational database or an object database. It is essentially a big, distributed, persistent, fault-tolerant hash table. This doesn’t make it ideal for all applications but does offer unique advantages, such as the ability to read and write scale horizontally, and the ability to combine in memory caching with the storage system so that a separate caching tier is not required. -
14
Walrus
Lightweight Python utilities for working with Redis
The purpose of walrus is to make working with Redis in Python a little easier. Rather than ask you to learn a new library, walrus subclasses and extends the popular redis-py client, allowing it to be used as a drop-in replacement. In addition to all the features in redis-py, walrus adds support for some newer commands, including full support for streams and consumer groups. Persistent structures implemented on top of Hashes. Supports secondary indexes to allow filtering on equality, inequality, ranges, less/greater-than, and a basic full-text search index. The full-text search features a boolean search query parser, porter stemmer, stop-word filtering, and optional double-metaphone implementation. -
15
YugabyteDB
The high-performance distributed SQL database for global apps
Microservices need a cloud-native relational database that is resilient, scalable, and geo-distributed. YugabyteDB powers your modern applications. Get instantly productive with a Postgres compatible RDBMS. YugabyteDB reuses PostgreSQL’s query layer and supports all advanced features. Scale-out and in with zero impact. Proven in production to scale beyond 300K TPS, over 100TB of data, and thousands of concurrent connections. Achieve continuous availability during infrastructure failures and on maintenance tasks such as software upgrades and distributed backups. Use powerful replication and data geo-partitioning capabilities to achieve the latency, resilience, and compliance your applications need. Deploy YugabyteDB in public, private, and hybrid cloud environments, on VMs, containers, or bare metal. Lower TCO for dev, staging, and production deployments. Powering a wide range of cloud-native workloads. Risk-free migration from on-prem to the cloud. -
16
ZeusDB Vector Database
Blazing-fast vector DB with similarity search and metadata filtering
ZeusDB is a vector database built for fast, scalable similarity search with strong production ergonomics. It combines high-performance approximate nearest neighbor indexes with clean APIs and metadata filtering so applications can retrieve semantically relevant items at low latency. The storage layer is designed for durability and growth, supporting sharding, replication, and background compaction while keeping query tails predictable. Developers get multiple ingestion paths—batch, streaming, and upsert—making it easy to keep embeddings synchronized as content changes. Hybrid search is a core design goal, allowing you to mix vector, keyword, and filter queries in a single request for practical relevance. Observability and safety round out the system, with metrics, tracing, and guardrails to manage recalls, deletions, and privacy-sensitive data at scale. -
17
atk4/data
Data Access PHP Framework for SQL & high-latency databases
ATK Data is a data persistence and modeling framework for PHP, developed as part of the Agile Toolkit. It provides a high-level abstraction for working with databases, making it easier to define and manipulate data models with minimal boilerplate code. It supports various SQL and NoSQL databases and integrates seamlessly with Agile UI and other PHP frameworks. -
18
data-diff
Efficiently diff rows across two different databases
We're excited to announce the launch of a new open-source product, data-diff that makes comparing datasets across databases fast at any scale. data-diff automates data quality checks for data replication and migration. In modern data platforms, data is constantly moving between systems, and at the modern data volume and complexity, systems go out of sync all the time. Until now, there has not been any tooling to ensure that when the data is correctly copied. Replicating data at scale, across hundreds of tables, with low latency and at a reasonable infrastructure cost is a hard problem, and most data teams we’ve talked to, have faced data quality issues in their replication processes. The hard truth is that the quality of the replication is the quality of the data. Since copying entire datasets in batch is often infeasible at the modern data scale, businesses rely on the Change Data Capture (CDC) approach of replicating data using a continuous stream of updates. -
19
doobie
Functional JDBC layer for Scala
doobie is a pure functional JDBC layer for Scala and Cats. It is not an ORM, nor is it a relational algebra; it simply provides a functional way to construct programs (and higher-level libraries) that use JDBC. For common use cases doobie provides a minimal but expressive high-level API. doobie is a Typelevel project. This means we embrace pure, typeful, functional programming, and provide a safe and friendly environment for teaching, learning, and contributing as described in the Scala Code of Conduct. Note that doobie is pre-1.0 software and is still undergoing active development. New versions are not binary compatible with prior versions, although in most cases user code will be source compatible. Starting with the 0.5.x we’re trying to be a bit more careful about versioning. If you want to build and run the tests for yourself, you’ll need a local postgresql database. -
20
elasticsearch-head
A web front end for an elastic search cluster
elasticsearch-head is a web front end for browsing and interacting with an Elastic Search cluster. elasticsearch-head is hosted and can be downloaded or forked at github. There are two ways of running and installing elasticsearch-head. Running as a plugin of ElasticSearch (this is the preferred method). And running as a standalone webapp. By default es-head will immediately attempt to connect to a cluster node at http://localhost:9200/. Enter a different node address in the connect box and click 'Connect' if required. A ClusterOverview, which shows the topology of your cluster and allows you to perform index and node level operations. A couple of search interfaces that allow you to query the cluster a retrieve results in raw json or tabular format. Several quick access tabs that show the status of the cluster. An input section that allows arbitrary call to the RESTful API to be made. This interface includes several options that can be combined to produce interesting results. -
21
gen
Converts a database into gorm structs and RESTful api
The gen tool produces a CRUD (Create, read, update and delete) REST API project template from a given database. The gen tool will connect to the db connection string analyze the database and generate the code based on the flags provided. By reading details from the database about the column structure, gen generates a go-compatible struct type with the required column names, data types, and annotations. It supports gorm tags and implements some usable methods. Generated data types include support for nullable columns sql.NullX types or guregu null.X types and the expected basic built-in go types. gen is based / inspired by the work of Seth Shelnutt's db2struct, and Db2Struct is based/inspired by the work of ChimeraCoder's gojson package gojson. Code generation for a complete CRUD rest project is possible with DAO crud functions, http handlers, makefile, sample server are available. -
22
go-clean-arch
Golang clean architecture based on Reading Uncle Bob's Clean Arch
Independent of Frameworks. The architecture does not depend on the existence of some library of feature-laden software. This allows you to use such frameworks as tools, rather than having to cram your system into their limited constraints. Testable. The business rules can be tested without the UI, Database, Web Server, or any other external element. Independent of UI. The UI can change easily, without changing the rest of the system. A Web UI could be replaced with a console UI, for example, without changing the business rules. Independent of Database. You can swap out Oracle or SQL Server, for Mongo, BigTable, CouchDB, or something else. Your business rules are not bound to the database. Independent of any external agency. In fact your business rules simply don’t know anything at all about the outside world. -
23
goleveldb
LevelDB key/value database in Go
This is an implementation of the LevelDB key/value database in the Go programming language. Package leveldb provides an implementation of LevelDB key/value database. OpenFile opens or creates a DB for the given path. The DB will be created if not exist, unless ErrorIfMissing is true. Also, if ErrorIfExist is true and the DB exist OpenFile will returns os.ErrExist error. OpenFile uses standard file-system backed storage implementation as described in the leveldb/storage package. OpenFile will return an error with type of ErrCorrupted if corruption is detected in the DB. Use errors.IsCorrupted to test whether an error is due to corruption. Corrupted DB can be recovered with Recover function. CompactRange compacts the underlying DB for the given key range. In particular, deleted and overwritten versions are discarded, and the data is rearranged to reduce the cost of operations needed to access the data. -
24
goqu
SQL builder and query library for golang
SQL builder and query library for golang. goqu is an expressive SQL builder and executor. Query builder, parameter interpolation (e.g SELECT * FROM "items" WHERE "id" = ? -> SELECT * FROM "items" WHERE "id" = 1). Built from the ground up with multiple dialects in mind. Insert, multi insert, update, and delete support. Scanning of rows to struct[s] or primitive value[s]. While goqu may support the scanning of rows into structs it is not intended to be used as an ORM if you are looking for common ORM features like associations, or hooks I would recommend looking at some of the great ORM libraries. The test suite requires a postgres, mysql and sqlserver databases. -
25
gormt
database to golang struct
mysql database to golang struct conversion tools base on gorm(v1/v2). You can automatically generate golang sturct from mysql database. big Camel-Case Name Rule, JSON tag. Database tables, column field annotation support. JSON tag and JSON tag output. gorm.Model Support export gorm.model. PRIMARY_KEY Specifies column as primary key. UNIQUE Specifies column as unique. NOT NULL Specifies column as NOT NULL. INDEX Create index with or without name, same name creates composite indexes. UNIQUE_INDEX Like INDEX, create unique index. Support foreign key related properties Support export gorm.model. Support function export (foreign key, association, index , unique and more)Support export function. model.Condition{} sql link. The exported function is only the auxiliary class function of Gorm, and calls Gorm completely.
