Alternatives to Chroma
Compare Chroma alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Chroma in 2026. Compare features, ratings, user reviews, pricing, and more from Chroma competitors and alternatives in order to make an informed decision for your business.
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1
DataHub
DataHub
DataHub Cloud is an event-driven AI & Data Context Platform that uses active metadata for real-time visibility across your entire data ecosystem. Unlike traditional data catalogs that provide outdated snapshots, DataHub Cloud instantly propagates changes, automatically enforces policies, and connects every data source across platforms with 100+ pre-built connectors. Built on an open source foundation with a thriving community of 13,000+ members, DataHub gives you unmatched flexibility to customize and extend without vendor lock-in. DataHub Cloud is a modern metadata platform with REST and GraphQL APIs that optimize performance for complex queries, essential for AI-ready data management and ML lifecycle support. -
2
MongoDB Atlas
MongoDB
The most innovative cloud database service on the market, with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more. MongoDB Atlas is the global cloud database service for modern applications. Deploy fully managed MongoDB across AWS, Google Cloud, and Azure with best-in-class automation and proven practices that guarantee availability, scalability, and compliance with the most demanding data security and privacy standards. The best way to deploy, run, and scale MongoDB in the cloud. MongoDB Atlas offers built-in security controls for all your data. Enable enterprise-grade features to integrate with your existing security protocols and compliance standards. With MongoDB Atlas, your data is protected with preconfigured security features for authentication, authorization, encryption, and more. -
3
RaimaDB
Raima
RaimaDB is an embedded time series database for IoT and Edge devices that can run in-memory. It is an extremely powerful, lightweight and secure RDBMS. Field tested by over 20 000 developers worldwide and has more than 25 000 000 deployments. RaimaDB is a high-performance, cross-platform embedded database designed for mission-critical applications, particularly in the Internet of Things (IoT) and edge computing markets. It offers a small footprint, making it suitable for resource-constrained environments, and supports both in-memory and persistent storage configurations. RaimaDB provides developers with multiple data modeling options, including traditional relational models and direct relationships through network model sets. It ensures data integrity with ACID-compliant transactions and supports various indexing methods such as B+Tree, Hash Table, R-Tree, and AVL-Tree. -
4
InterBase
Embarcadero
Ultrafast, scalable, embeddable SQL database with commercial-grade data security, disaster recovery, and change synchronization. Cross-platform, zero-install, embedded database as a direct-access library. Cross-platform, zero-install, embedded database with database-level and column-level AES and DES encryption. Concurrent applications/client access to the database on Windows with database-level and column-level AES and DES encryption. Ultrafast, scalable, SQL server database for Windows and Linux with commercial-grade data security, disaster recovery and change synchronization. Attacks on databases and loss of data can be costly and lead to loss of customers’ trust (and business), regulatory action, and heavy fines. InterBase provides over-the-wire and at-rest encryption, separate security login, and role-based user security. InterBase maintains full on-disk encryption while adding negligible overhead to database speed and performance. -
5
Pinecone
Pinecone
The AI Knowledge Platform. The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Developer-friendly, fully managed, and easily scalable without infrastructure hassles. Once you have vector embeddings, manage and search through them in Pinecone to power semantic search, recommenders, and other applications that rely on relevant information retrieval. Ultra-low query latency, even with billions of items. Give users a great experience. Live index updates when you add, edit, or delete data. Your data is ready right away. Combine vector search with metadata filters for more relevant and faster results. Launch, use, and scale your vector search service with our easy API, without worrying about infrastructure or algorithms. We'll keep it running smoothly and securely. -
6
Qdrant
Qdrant
Qdrant is a vector similarity engine & vector database. It deploys as an API service providing search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more! Provides the OpenAPI v3 specification to generate a client library in almost any programming language. Alternatively utilise ready-made client for Python or other programming languages with additional functionality. Implement a unique custom modification of the HNSW algorithm for Approximate Nearest Neighbor Search. Search with a State-of-the-Art speed and apply search filters without compromising on results. Support additional payload associated with vectors. Not only stores payload but also allows filter results based on payload values. -
7
Zilliz Cloud
Zilliz
Zilliz Cloud is a fully managed vector database based on the popular open-source Milvus. Zilliz Cloud helps to unlock high-performance similarity searches with no previous experience or extra effort needed for infrastructure management. It is ultra-fast and enables 10x faster vector retrieval, a feat unparalleled by any other vector database management system. Zilliz includes support for multiple vector search indexes, built-in filtering, and complete data encryption in transit, a requirement for enterprise-grade applications. Zilliz is a cost-effective way to build similarity search, recommender systems, and anomaly detection into applications to keep that competitive edge.Starting Price: $0 -
8
Faiss
Meta
Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research.Starting Price: Free -
9
Embeddinghub
Featureform
Operationalize your embeddings with one simple tool. Experience a comprehensive database designed to provide embedding functionality that, until now, required multiple platforms. Elevate your machine learning quickly and painlessly through Embeddinghub. Embeddings are dense, numerical representations of real-world objects and relationships, expressed as vectors. They are often created by first defining a supervised machine learning problem, known as a "surrogate problem." Embeddings intend to capture the semantics of the inputs they were derived from, subsequently getting shared and reused for improved learning across machine learning models. Embeddinghub lets you achieve this in a streamlined, intuitive way.Starting Price: Free -
10
LanceDB
LanceDB
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.Starting Price: $16.03 per month -
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MyScale
MyScale
MyScale is an innovative AI database that seamlessly integrates vector search with SQL analytics, delivering a comprehensive, fully managed, and high-performance solution. Key Features: - Superior Data Capacity and Performance: Each MyScale pod supports 5 million 768-dimensional data points with exceptional accuracy, enabling over 150 queries per second (QPS). - Rapid Data Ingestion: Import up to 5 million data points in under 30 minutes, reducing waiting time and enabling faster utilization of your vector data. - Flexible Indexing: MyScale allows you to create multiple tables with unique vector indexes, efficiently managing diverse vector data within a single cluster. - Effortless Data Import and Backup: Seamlessly import/export data from/to S3 or other compatible storage systems, ensuring smooth data management and backup processes. With MyScale, unleash the power of advanced AI database capabilities for efficient and effective data analysis. -
12
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. -
13
VectorDB
VectorDB
VectorDB is a lightweight Python package for storing and retrieving text using chunking, embedding, and vector search techniques. It provides an easy-to-use interface for saving, searching, and managing textual data with associated metadata and is designed for use cases where low latency is essential. Vector search and embeddings are essential when working with large language models because they enable efficient and accurate retrieval of relevant information from massive datasets. By converting text into high-dimensional vectors, these techniques allow for quick comparisons and searches, even when dealing with millions of documents. This makes it possible to find the most relevant results in a fraction of the time it would take using traditional text-based search methods. Additionally, embeddings capture the semantic meaning of the text, which helps improve the quality of the search results and enables more advanced natural language processing tasks.Starting Price: Free -
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Weaviate
Weaviate
Weaviate is an open-source vector database. It allows you to store data objects and vector embeddings from your favorite ML-models, and scale seamlessly into billions of data objects. Whether you bring your own vectors or use one of the vectorization modules, you can index billions of data objects to search through. Combine multiple search techniques, such as keyword-based and vector search, to provide state-of-the-art search experiences. Improve your search results by piping them through LLM models like GPT-3 to create next-gen search experiences. Beyond search, Weaviate's next-gen vector database can power a wide range of innovative apps. Perform lightning-fast pure vector similarity search over raw vectors or data objects, even with filters. Combine keyword-based search with vector search techniques for state-of-the-art results. Use any generative model in combination with your data, for example to do Q&A over your dataset.Starting Price: Free -
15
txtai
NeuML
txtai is an all-in-one open source embeddings database designed for semantic search, large language model orchestration, and language model workflows. It unifies vector indexes (both sparse and dense), graph networks, and relational databases, providing a robust foundation for vector search and serving as a powerful knowledge source for LLM applications. With txtai, users can build autonomous agents, implement retrieval augmented generation processes, and develop multi-modal workflows. Key features include vector search with SQL support, object storage integration, topic modeling, graph analysis, and multimodal indexing capabilities. It supports the creation of embeddings for various data types, including text, documents, audio, images, and video. Additionally, txtai offers pipelines powered by language models that handle tasks such as LLM prompting, question-answering, labeling, transcription, translation, and summarization.Starting Price: Free -
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Milvus
Zilliz
Vector database built for scalable similarity search. Open-source, highly scalable, and blazing fast. Store, index, and manage massive embedding vectors generated by deep neural networks and other machine learning (ML) models. With Milvus vector database, you can create a large-scale similarity search service in less than a minute. Simple and intuitive SDKs are also available for a variety of different languages. Milvus is hardware efficient and provides advanced indexing algorithms, achieving a 10x performance boost in retrieval speed. Milvus vector database has been battle-tested by over a thousand enterprise users in a variety of use cases. With extensive isolation of individual system components, Milvus is highly resilient and reliable. The distributed and high-throughput nature of Milvus makes it a natural fit for serving large-scale vector data. Milvus vector database adopts a systemic approach to cloud-nativity, separating compute from storage.Starting Price: Free -
17
Couchbase
Couchbase
Unlike other NoSQL databases, Couchbase provides an enterprise-class, multicloud to edge database that offers the robust capabilities required for business-critical applications on a highly scalable and available platform. As a distributed cloud-native database, Couchbase runs in modern dynamic environments and on any cloud, either customer-managed or fully managed as-a-service. Couchbase is built on open standards, combining the best of NoSQL with the power and familiarity of SQL, to simplify the transition from mainframe and relational databases. Couchbase Server is a multipurpose, distributed database that fuses the strengths of relational databases such as SQL and ACID transactions with JSON’s versatility, with a foundation that is extremely fast and scalable. It’s used across industries for things like user profiles, dynamic product catalogs, GenAI apps, vector search, high-speed caching, and much more. -
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Vespa
Vespa.ai
Vespa is forBig Data + AI, online. At any scale, with unbeatable performance. To build production-worthy online applications that combine data and AI, you need more than point solutions: You need a platform that integrates data and compute to achieve true scalability and availability - and which does this without limiting your freedom to innovate. Only Vespa does this. Vespa is a fully featured search engine and vector database. It supports vector search (ANN), lexical search, and search in structured data, all in the same query. Users can easily build recommendation applications on Vespa. Integrated machine-learned model inference allows you to apply AI to make sense of your data in real-time. Together with Vespa's proven scaling and high availability, this empowers you to create production-ready search applications at any scale and with any combination of features.Starting Price: Free -
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BabyAGI
BabyAGI
This Python script is an example of an AI-powered task management system. The system uses OpenAI and Chroma to create, prioritize, and execute tasks. The main idea behind this system is that it creates tasks based on the result of previous tasks and a predefined objective. The script then uses OpenAI's natural language processing (NLP) capabilities to create new tasks based on the objective, and Chroma to store and retrieve task results for context. This is a pared-down version of the original Task-Driven Autonomous Agent. The script works by running an infinite loop that does the following steps: 1. Pulls the first task from the task list. 2. Sends the task to the execution agent, which uses OpenAI's API to complete the task based on the context. 3. Enriches the result and stores it in Chroma. 4. Creates new tasks and reprioritizes the task list based on the objective and the result of the previous task.Starting Price: Free -
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ArcadeDB
ArcadeDB
ArcadeDB is an open-source, next-generation multi-model database. Forget Polyglot Persistence — store graphs, documents, key-value pairs, search engine indexes, vectors, and time-series data all in one database with native support for every model. No translation layers, no performance penalties. Process over 10 million records per second. Traversal speed stays constant whether your database has hundreds or billions of records. Query in the language you prefer: SQL, Cypher, Gremlin, GraphQL, MongoDB API, or Java. Deploy ArcadeDB embedded in your JVM application, on a standalone server, or distributed across multiple nodes with Raft Consensus for high availability. Fully ACID-compliant. Super lightweight. Apache 2.0 licensed — free for production and commercial use.Starting Price: Free -
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H2
H2
Welcome to H2, the Java SQL database. In embedded mode, an application opens a database from within the same JVM using JDBC. This is the fastest and easiest connection mode. The disadvantage is that a database may only be open in one virtual machine (and class loader) at any time. As in all modes, both persistent and in-memory databases are supported. There is no limit on the number of database open concurrently, or on the number of open connections. The mixed mode is a combination of the embedded and the server mode. The first application that connects to a database does that in embedded mode, but also starts a server so that other applications (running in different processes or virtual machines) can concurrently access the same data. The local connections are as fast as if the database is used in just the embedded mode, while the remote connections are a bit slower. -
22
Flowise
Flowise AI
Flowise is an open-source platform that enables developers and teams to build AI agents and LLM-powered applications through a visual interface. The platform provides modular building blocks that allow users to create everything from simple chatbot workflows to complex multi-agent systems. With its drag-and-drop design environment, developers can rapidly prototype and deploy AI-powered applications without extensive coding. Flowise supports integrations with more than 100 large language models, embeddings, and vector databases. It also includes features such as human-in-the-loop workflows, observability tools, and execution tracing for monitoring agent behavior. Developers can extend applications through APIs, SDKs, and embedded chat interfaces using TypeScript or Python. By combining visual development tools with scalable infrastructure, Flowise simplifies the process of building and deploying production-ready AI agents.Starting Price: Free -
23
Perst
McObject
Perst is McObject’s open source, dual license, object-oriented embedded database system (ODBMS). It is available in one edition developed as an all-Java embedded database, and another implemented in C# (for Microsoft .NET Framework applications). Perst gives developers the ability to store, sort, and retrieve objects in their applications with maximum speed and with low memory and storage overhead while leveraging the object-oriented paradigm of Java and C#. In the TestIndex and PolePosition benchmarks, Perst displays one of its strongest features: its significant performance advantage over Java and .NET embedded database alternatives. Perst stores data directly in Java and .NET objects, eliminating the translation required for storage in relational and object-relational databases. This boosts run-time performance. Perst’s core consists of only five thousand lines of code. The small footprint imposes minimal demands on system resources.Starting Price: Free -
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Empress RDBMS
Empress Software
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. -
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Mixedbread
Mixedbread
Mixedbread is a fully-managed AI search engine that allows users to build production-ready AI search and Retrieval-Augmented Generation (RAG) applications. It offers a complete AI search stack, including vector stores, embedding and reranking models, and document parsing. Users can transform raw data into intelligent search experiences that power AI agents, chatbots, and knowledge systems without the complexity. It integrates with tools like Google Drive, SharePoint, Notion, and Slack. Its vector stores enable users to build production search engines in minutes, supporting over 100 languages. Mixedbread's embedding and reranking models have achieved over 50 million downloads and outperform OpenAI in semantic search and RAG tasks while remaining open-source and cost-effective. The document parser extracts text, tables, and layouts from PDFs, images, and complex documents, providing clean, AI-ready content without manual preprocessing. -
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MySQL
Oracle
MySQL is the world's most popular open source database. With its proven performance, reliability, and ease-of-use, MySQL has become the leading database choice for web-based applications, used by high profile web properties including Facebook, Twitter, YouTube, and all five of the top five websites*. Additionally, it is an extremely popular choice as embedded database, distributed by thousands of ISVs and OEMs.Starting Price: Free -
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TopK
TopK
TopK is a serverless, cloud-native, document database built for powering search applications. It features native support for both vector search (vectors are simply another data type) and keyword search (BM25-style) in a single, unified system. With its powerful query expression language, TopK enables you to build reliable search applications (semantic search, RAG, multi-modal, you name it) without juggling multiple databases or services. Our unified retrieval engine will evolve to support document transformation (automatically generate embeddings), query understanding (parse metadata filters from user query), and adaptive ranking (provide more relevant results by sending “relevance feedback” back to TopK) under one unified roof. -
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HyperSQL DataBase
The hsql Development Group
HSQLDB (HyperSQL DataBase) is the leading SQL relational database system written in Java. It offers a small, fast multithreaded and transactional database engine with in-memory and disk-based tables and supports embedded and server modes. It includes a powerful command line SQL tool and simple GUI query tools. HSQLDB supports the widest range of SQL Standard features seen in any open source database engine: SQL:2016 core language features and an extensive list of SQL:2016 optional features. It supports full Advanced ANSI-92 SQL with only two exceptions. Many extensions to the Standard, including syntax compatibility modes and features of other popular database engines, are also supported. -
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Metal
Metal
Metal is your production-ready, fully-managed, ML retrieval platform. Use Metal to find meaning in your unstructured data with embeddings. Metal is a managed service that allows you to build AI products without the hassle of managing infrastructure. Integrations with OpenAI, CLIP, and more. Easily process & chunk your documents. Take advantage of our system in production. Easily plug into the MetalRetriever. Simple /search endpoint for running ANN queries. Get started with a free account. Metal API Keys to use our API & SDKs. With your API Key, you can use authenticate by populating the headers. Learn how to use our Typescript SDK to implement Metal into your application. Although we love TypeScript, you can of course utilize this library in JavaScript. Mechanism to fine-tune your spp programmatically. Indexed vector database of your embeddings. Resources that represent your specific ML use-case.Starting Price: $25 per month -
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ChromaWay
ChromaWay
ChromaWay built relational blockchain because we believe it is the best way to make blockchain applications which are practical and offer a strong balance between cost and benefit. We work with partners, entrepreneurs and enthusiasts to bring relational blockchain to bear on real problems across a range of industries. ChromaWay has partnered with the government of Andhra Pradesh to build a blockchain-powered system for land registration. The solution has the potential to eliminate fraud and errors, and greatly reduce the administrative burden of land registration and title transfer. A blockchain must be able to add data in a secure way, but if it acts as a database, surely getting that data out again is equally important. The strictness of the validity rules in "traditional" blockchains (NoSQL linked lists) means that they have only the most primitive querying support. -
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Deep Lake
activeloop
Generative AI may be new, but we've been building for this day for the past 5 years. Deep Lake thus combines the power of both data lakes and vector databases to build and fine-tune enterprise-grade, LLM-based solutions, and iteratively improve them over time. Vector search does not resolve retrieval. To solve it, you need a serverless query for multi-modal data, including embeddings or metadata. Filter, search, & more from the cloud or your laptop. Visualize and understand your data, as well as the embeddings. Track & compare versions over time to improve your data & your model. Competitive businesses are not built on OpenAI APIs. Fine-tune your LLMs on your data. Efficiently stream data from remote storage to the GPUs as models are trained. Deep Lake datasets are visualized right in your browser or Jupyter Notebook. Instantly retrieve different versions of your data, materialize new datasets via queries on the fly, and stream them to PyTorch or TensorFlow.Starting Price: $995 per month -
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eXtremeDB
McObject
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 -
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ITTIA DB
ITTIA
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. -
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IBM Informix
IBM
IBM Informix® is a fast and flexible database with the ability to seamlessly integrate SQL, NoSQL/JSON, and time series and spatial data. Its versatility and ease of use make Informix a preferred solution for a wide range of environments, from enterprise data warehouses to individual application development. Also, with its small footprint and self-managing capabilities, Informix is well suited for embedded data-management solutions. IoT data demands robust processing and integration capabilities. Informix offers a hybrid database system with minimal administrative requirements and memory footprint combined with powerful functionality. Key features make Informix ideal for multi-tiered architectures that require processing at the device level, at gateway layers and in the cloud. Native encryption to protect data at rest and in motion. Support for flexible schema, multiple APIs and configurations. -
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RocksDB
RocksDB
RocksDB uses a log structured database engine, written entirely in C++, for maximum performance. Keys and values are just arbitrarily-sized byte streams. RocksDB is optimized for fast, low latency storage such as flash drives and high-speed disk drives. RocksDB exploits the full potential of high read/write rates offered by flash or RAM. RocksDB provides basic operations such as opening and closing a database, reading and writing to more advanced operations such as merging and compaction filters. RocksDB is adaptable to different workloads. From database storage engines such as MyRocks to application data caching to embedded workloads, RocksDB can be used for a variety of data needs. -
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OneStep-JV
Business Control Systems
POS system brings the most advanced technology available in a full-featured suite of applications for retailers and distributors. The OneStep-JV™ Point of Sale system combines the power and flexibility of Java and Oracle. Written in Java with Oracle as the embedded database at its foundation, OneStep-JV™ point of sale systems bring the most advanced and reliable technology and inventory management software available to achieve operational stability and cross-platform portability for retailers and distributors. The use of Java enables the operation of OneStep-JV™ POS systems on single-user computers, small and very large-scale networks and portable devices like Palm Tops running over a multitude of operating systems such as Windows and Windows Networks, Novell, Unix and Linux. The stability of Oracle gives OneStep-JV™ POS systems a resilient database foundation designed with auto-recovery features to enable database and inventory control software integrity. -
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Audio AI Dynamics
Audio AI Dynamics
🎶 Audio AI Dynamics (AAID): AI-powered tools for music creators 🎶 A suite of web-based audio tools designed to empower musicians, producers, and audio enthusiasts. Whether you're a pro or just starting out, Audio AI Dynamics offers a range of features to enhance your music workflow. 🎧 🔊 Features: Music Analyzer: Break down your audio with in-depth analysis to discover BPM, chords, chroma, and more. BPM Tapper: Easily find the tempo of your favorite tracks by tapping along. Audio Trimmer: Quick and precise audio editing with our seamless trimming tool. Voice Recorder: Sing, record, and merge your voice with backing tracks in real time. HPCP Chroma & Chord Detection: Analyze harmonic content and detect chords effortlessly. Online Metronome: Stay in sync with our fully customizable metronome. Genre Finder: Realtime song genre finder.Starting Price: $0 -
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Marqo
Marqo
Marqo is more than a vector database, it's an end-to-end vector search engine. Vector generation, storage, and retrieval are handled out of the box through a single API. No need to bring your own embeddings. Accelerate your development cycle with Marqo. Index documents and begin searching in just a few lines of code. Create multimodal indexes and search combinations of images and text with ease. Choose from a range of open source models or bring your own. Build interesting and complex queries with ease. With Marqo you can compose queries with multiple weighted components. With Marqo, input pre-processing, machine learning inference, and storage are all included out of the box. Run Marqo in a Docker image on your laptop or scale it up to dozens of GPU inference nodes in the cloud. Marqo can be scaled to provide low-latency searches against multi-terabyte indexes. Marqo helps you configure deep-learning models like CLIP to pull semantic meaning from images.Starting Price: $86.58 per month -
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Oracle Berkeley DB
Oracle
Berkeley DB is a family of embedded key-value database libraries providing scalable high-performance data management services to applications. The Berkeley DB products use simple function-call APIs for data access and management. Berkeley DB enables the development of custom data management solutions, without the overhead traditionally associated with such custom projects. Berkeley DB provides a collection of well-proven building-block technologies that can be configured to address any application need from the hand-held device to the data center, from a local storage solution to a world-wide distributed one, from kilobytes to petabytes. -
40
Actian Zen
Actian
Actian Zen is an embedded, high-performance, and low-maintenance database management system designed for edge applications, mobile devices, and IoT environments. It offers a seamless integration of SQL and NoSQL data models, providing flexibility for developers working with structured and unstructured data. Actian Zen is known for its small footprint, scalability, and high reliability, making it ideal for resource-constrained environments where consistent performance and minimal administrative overhead are essential. With built-in security features and a self-tuning architecture, it supports real-time data processing and analytics without the need for constant monitoring or maintenance. Actian Zen is widely used in industries like healthcare, retail, and manufacturing, where edge computing and distributed data environments are critical for business operations. -
41
Astra DB
DataStax
Astra DB from DataStax is vector database for developers that need to get accurate Generative AI applications into production, quickly and efficiently. Built on Apache Cassandra, Astra DB is the only vector database that can make vector updates immediately available to applications and scale to the largest real-time data and streaming workloads, securely on any cloud. Astra DB offers unprecedented serverless, pay as you go pricing and the flexibility of multi-cloud and open-source. You can store up to 80GB and/or perform 20 million operations per month. Securely connect to VPC peering and private links. Manage your encryption keys with your own key management and SAML SSO secure account accessibility. You can deploy on AWS, GCP, or Azure while still maintaining open-source Cassandra compatibility. -
42
Cloudflare Vectorize
Cloudflare
Begin building for free in minutes. Vectorize enables fast & cost-effective vector storage to power your search & AI Retrieval Augmented Generation (RAG) applications. Avoid tool sprawl & reduce total cost of ownership, Vectorize seamlessly integrates with Cloudflare’s AI developer platform and AI gateway for centralized development, monitoring & control of AI applications on a global scale. Vectorize is a globally distributed vector database that enables you to build full-stack, AI-powered applications with Cloudflare Workers AI. Vectorize makes querying embeddings, representations of values or objects like text, images, and audio that are designed to be consumed by machine learning models and semantic search algorithms, faster, easier, and more affordable. Search, similarity, recommendation, classification & anomaly detection based on your own data. Improved results & faster search. String, number & boolean types are supported. -
43
Nomic Atlas
Nomic AI
Atlas integrates into your workflow by organizing text and embedding datasets into interactive maps for exploration in a web browser. You shouldn’t have to scroll through Excel files, log Dataframes and page through lists to understand your data. Atlas automatically reads, organizes and summarizes your collections of documents surfacing trends and patterns. Atlas’ pre-organized data interface allows you to quickly surface pathologies and dirty data that can jeopardize your AI projects. Label and tag your data while you clean it with immediate sync to your Jupyter Notebook. Vector databases enable powerful applications such as recommendation systems but are notoriously hard to interpret. Atlas stores, visualizes and lets you search through all of your vectors in the same API.Starting Price: $50 per month -
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Vectorize
Vectorize
Vectorize is a platform designed to transform unstructured data into optimized vector search indexes, facilitating retrieval-augmented generation pipelines. It enables users to import documents or connect to external knowledge management systems, allowing Vectorize to extract natural language suitable for LLMs. The platform evaluates multiple chunking and embedding strategies in parallel, providing recommendations or allowing users to choose their preferred methods. Once a vector configuration is selected, Vectorize deploys it into a real-time vector pipeline that automatically updates with any data changes, ensuring accurate search results. The platform offers connectors to various knowledge repositories, collaboration platforms, and CRMs, enabling seamless integration of data into generative AI applications. Additionally, Vectorize supports the creation and updating of vector indexes in preferred vector databases.Starting Price: $0.57 per hour -
45
CamTrackAR
FXHome
The world’s first mobile virtual production studio for iOS. Capture video and 3D tracking data simultaneously in CamTrackAR, and get dynamic 3D model placement, world-leading chroma key technology, and the ability to import virtual backgrounds for professional pre-visualization. Perfect for professionals looking for pre-visualization options on set, and any video creator or VFX artist wanting to speed up their post-production workflow. We believe in creativity, and making powerful tools accessible to everyone. What started as a big idea on a little budget, has grown into a movement on a global scale. From video editing to photography tools, our software powers countless creative projects worldwide. CamTrackAR is the world’s first app that allows you to create virtual productions using iOS. Use world-leading chroma key technology alongside 3D model import and automatic camera tracking to pre-visualize virtual production scenes right on set. -
46
solidDB
UNICOM Systems
solidDB is known worldwide for delivering data with extreme speed. There are millions of deployments of solidDB in telecommunications networks, enterprise applications, and embedded software & systems. Market leaders such as Cisco, HP, Alcatel, Nokia and Siemens rely on it for their mission-critical applications. By keeping critical data in memory, rather than on disk, solidDB can perform significantly faster than conventional databases. It helps applications achieve throughput of hundreds of thousands to millions of transactions per second with response times measured in microseconds. Beyond game-changing performance, solidDB also provides built-in data availability features that help sustain uptime, prevent data loss and accelerate recovery. Additionally, solidDB supports administrators with the flexibility to tailor the software to precise application needs and features designed to simplify deployment and administration, helping drive down the total cost of ownership (TCO). -
47
VideoCap Pro SDK ActiveX
Viscom Software
For Windows Developers who need to view IP Camera, add video capture with overlay text, image, chroma key effect, face detection, motion detection with C++ , C#, VB.NET , VB, Delphi, Vfp, Ms Access, Labview. -
48
ConfidentialMind
ConfidentialMind
We've done the work of bundling and pre-configuring all the components you need for building solutions and integrating LLMs directly into your business processes. With ConfidentialMind you can jump right into action. Deploys an endpoint for the most powerful open source LLMs like Llama-2, turning it into an internal LLM API. Imagine ChatGPT in your very own cloud. This is the most secure solution possible. Connects the rest of the stack with the APIs of the largest hosted LLM providers like Azure OpenAI, AWS Bedrock, or IBM. ConfidentialMind deploys a playground UI based on Streamlit with a selection of LLM-powered productivity tools for your company such as writing assistants and document analysts. Includes a vector database, critical components for the most common LLM applications for shifting through massive knowledge bases with thousands of documents efficiently. Allows you to control the access to the solutions your team builds and what data the LLMs have access to. -
49
VelocityDB
VelocityDB
VelocityDB is a database engine like no other. It can store data faster and more efficiently than any other solution at a fraction of the cost of other database engines. It stores .NET objects as they are with no mapping to tables, JSON or XML. VelocityGraph is an add on open source property graph database that can be used in conjunction with the VelocityDB object database. Object and graph database engine VelocityDB is a C# .NET noSQL object fatabase, extended as graph database is VelocityGraph. World’s fastest most scalable & flexible database. A bug reported with a reproducible test case is usually fixed within a week. The most important benefit is the flexibility that this database system provides. No other types of database system lets you fine tune your application to the finest details. Using VelocityDB, you can choose the best possible data structures for your application. You can control where you place the data persistently and how it's indexed and accessed.Starting Price: $200 per 6 moths -
50
BilberryDB
BilberryDB
BilberryDB is an enterprise-grade vector-database platform designed for building AI applications that handle multimodal data, including images, video, audio, 3D models, tabular data, and text, across one unified system. It supports lightning-fast similarity search and retrieval via embeddings, allows few-shot or no-code workflows to create powerful search/classification capabilities without large labelled datasets, and offers a developer SDK (such as TypeScript) as well as a visual builder for non-technical users. The platform emphasises sub-second query performance at scale, seamless ingestion of diverse data types, and rapid deployment of vector-search-enabled apps (“Deploy as an App”) so organisations can build AI-driven search, recommendation, classification, or content-discovery systems without building infrastructure from scratch.Starting Price: Free
