Alternatives to Chroma

Searching and analyzing structured data is easy; however, over 80% of generated data is unstructured, requiring a different approach. Machine learning converts unstructured data into high-dimensional vectors of numerical values, which makes it possible to find patterns or relationships within that data type. Unfortunately, traditional databases were never meant to store vectors or embeddings and can not meet unstructured data's scalability and performance requirements. Zilliz Cloud is a cloud-native vector database that stores, indexes, and searches for billions of embedding vectors to power enterprise-grade similarity search, recommender systems, anomaly detection, and more. Zilliz Cloud, built on the popular open-source vector database Milvus, allows for easy integration with vectorizers from OpenAI, Cohere, HuggingFace, and other popular models. Purpose-built to solve the challenge of managing billions of embeddings, Zilliz Cloud makes it easy to build applications for scale.

Artificial intelligence long-term memory The Pinecone vector database makes building high-performance vector search apps easy. Fully managed and developer-friendly, the database is easily scalable without any infrastructure problems. Once you have vector embeddings created, you can search and manage them in Pinecone to power semantic searches, recommenders, or other applications that rely upon relevant information retrieval. Even with billions of items, ultra-low query latency Provide a great user experience. You can add, edit, and delete data via live index updates. Your data is available immediately. For more relevant and quicker results, combine vector search with metadata filters. Our API makes it easy to launch, use, scale, and scale your vector searching service without worrying about infrastructure. It will run smoothly and securely.

One tool allows you to operationalize your embeddings. A comprehensive database that provides embedding functionality previously unavailable on multiple platforms is now available to you. Embeddinghub makes it easy to accelerate your machine learning. Embeddings are dense numerical representations of real world objects and relationships. They can be expressed as vectors. They are often created by first defining an unsupervised machine learning problem, also known as a "surrogate issue". Embeddings are intended to capture the semantics from the inputs they were derived. They can then be shared and reused for better learning across machine learning models. This is possible with Embeddinghub in an intuitive and streamlined way.

Qdrant is a vector database and similarity engine. It is an API service that allows you to search for the closest high-dimensional vectors. Qdrant allows embeddings and neural network encoders to be transformed into full-fledged apps for matching, searching, recommending, etc. This specification provides the OpenAPI version 3 specification to create a client library for almost any programming language. You can also use a ready-made client for Python, or other programming languages that has additional functionality. For Approximate Nearest Neighbor Search, you can make a custom modification to the HNSW algorithm. Search at a State of the Art speed and use search filters to maximize results. Additional payload can be associated with vectors. Allows you to store payload and filter results based upon payload values.

Faiss is a library that allows for efficient similarity searches and clustering dense vectors. It has algorithms that can search for vectors of any size. It also includes supporting code for parameter tuning and evaluation. Faiss is written entirely in C++ and includes wrappers for Python. The GPU is home to some of the most powerful algorithms. It was developed by Facebook AI Research.

LlamaIndex, a "dataframework", is designed to help you create LLM apps. Connect semi-structured API data like Slack or Salesforce. LlamaIndex provides a flexible and simple data framework to connect custom data sources with large language models. LlamaIndex is a powerful tool to enhance your LLM applications. Connect your existing data formats and sources (APIs, PDFs, documents, SQL etc.). Use with a large-scale language model application. Store and index data for different uses. Integrate downstream vector stores and database providers. LlamaIndex is a query interface which accepts any input prompts over your data, and returns a knowledge augmented response. Connect unstructured data sources, such as PDFs, raw text files and images. Integrate structured data sources such as Excel, SQL etc. It provides ways to structure data (indices, charts) so that it can be used with LLMs.

Weaviate is an open source vector database. It allows you to store vector embeddings and data objects from your favorite ML models, and scale seamlessly into billions upon billions of data objects. You can index billions upon billions of data objects, whether you use the vectorization module or your own vectors. Combining multiple search methods, such as vector search and keyword-based search, can create state-of-the art search experiences. To improve your search results, pipe them through LLM models such as GPT-3 to create next generation search experiences. Weaviate's next generation vector database can be used to power many innovative apps. You can perform a lightning-fast, pure vector similarity search on raw vectors and data objects. Combining keyword-based and vector search techniques will yield state-of the-art results. You can combine any generative model with your data to do Q&A, for example, over your dataset.

MyScale is a cutting-edge AI database that combines vector search with SQL analytics, offering a seamless, fully managed, and high-performance solution. Key features of MyScale include: - Enhanced data capacity and performance: Each standard MyScale pod supports 5 million 768-dimensional data points with exceptional accuracy, delivering over 150 QPS. - Swift data ingestion: Ingest up to 5 million data points in under 30 minutes, minimizing wait times and enabling faster serving of your vector data. - Flexible index support: MyScale allows you to create multiple tables, each with its own unique vector indexes, empowering you to efficiently manage heterogeneous vector data within a single MyScale cluster. - Seamless data import and backup: Effortlessly import and export data from and to S3 or other compatible storage systems, ensuring smooth data management and backup processes. With MyScale, you can harness the power of advanced AI database capabilities for efficient and effective data analysis.

A vector database designed for scalable similarity searches. Open-source, highly scalable and lightning fast. Massive embedding vectors created by deep neural networks or other machine learning (ML), can be stored, indexed, and managed. Milvus vector database makes it easy to create large-scale similarity search services in under a minute. For a variety languages, there are simple and intuitive SDKs. Milvus is highly efficient on hardware and offers advanced indexing algorithms that provide a 10x speed boost in retrieval speed. Milvus vector database is used in a variety a use cases by more than a thousand enterprises. Milvus is extremely resilient and reliable due to its isolation of individual components. Milvus' distributed and high-throughput nature makes it an ideal choice for large-scale vector data. Milvus vector database uses a systemic approach for cloud-nativity that separates compute and storage.

Marqo is a complete vector search engine. It's more than just a database. A single API handles vector generation, storage and retrieval. No need to embed your own embeddings. Marqo can accelerate your development cycle. In just a few lines, you can index documents and start searching. Create multimodal indexes, and search images and text combinations with ease. You can choose from a variety of open-source models or create your own. Create complex and interesting queries with ease. Marqo allows you to compose queries that include multiple weighted components. Marqo includes input pre-processing and machine learning inference as well as storage. Marqo can be run as a Docker on your laptop, or scaled up to dozens GPU inference nodes. Marqo is scalable to provide low latency searches on multi-terabyte indices. Marqo allows you to configure deep-learning models such as CLIP for semantic meaning extraction from images.

Metal is a fully-managed, production-ready ML retrieval platform. Metal embeddings can help you find meaning in unstructured data. Metal is a managed services that allows you build AI products without having to worry about managing infrastructure. Integrations with OpenAI and CLIP. Easy processing & chunking of your documents. Profit from our system in production. MetalRetriever is easily pluggable. Simple /search endpoint to run ANN queries. Get started for free. Metal API Keys are required to use our API and SDKs. Authenticate by populating headers with your API Key. Learn how to integrate Metal into your application using our Typescript SDK. You can use this library in JavaScript as well, even though we love TypeScript. Fine-tune spp programmatically. Indexed vector data of your embeddings. Resources that are specific to your ML use case.

Vespa is forBig Data + AI, online. At any scale, with unbeatable performance. 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. Integrated machine-learned model inference allows you to apply AI to make sense of your data in real-time. Users build recommendation applications on Vespa, typically combining fast vector search and filtering with evaluation of machine-learned models over the items. 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. 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.

We've been working on Generative AI for 5 years. Deep Lake combines the power and flexibility of vector databases and data lakes to create enterprise-grade LLM-based solutions and refine them over time. Vector search does NOT resolve retrieval. You need a serverless search for multi-modal data including embeddings and metadata to solve this problem. You can filter, search, and more using the cloud, or your laptop. Visualize your data and embeddings to better understand them. Track and compare versions to improve your data and your model. OpenAI APIs are not the foundation of competitive businesses. Your data can be used to fine-tune LLMs. As models are being trained, data can be efficiently streamed from remote storage to GPUs. Deep Lake datasets can be visualized in your browser or Jupyter Notebook. Instantly retrieve different versions and materialize new datasets on the fly via queries. Stream them to PyTorch, TensorFlow, or Jupyter Notebook.

Astra DB from DataStax is a real-time vector database as a service for developers that need to get accurate Generative AI applications into production, fast. Astra DB gives you a set of elegant APIs supporting multiple languages and standards, powerful data pipelines and complete ecosystem integrations. Astra DB enables you to quickly build Gen AI applications on your real-time data for more accurate AI that you can deploy in production. 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. SAML SSO secure account accessibility. You can deploy on Amazon, Google Cloud, or Microsoft Azure while still compatible with open-source Apache Cassandra.

Postgres: Open-source vector similarity search Supports exact and approximate closest neighbor search for L2 distances, inner product and cosine distances.

Create and manage AI applications without the need to move data to complex vector databases and pipelines. Integrate AI, vector search and real-time inference directly with your database. Python is all you need. All your AI models can be deployed in a single, scalable deployment. The AI models and APIs are automatically updated as new data is processed. You don't need to duplicate your data or create an additional database to use vector searching and build on it. SuperDuperDB allows vector search within your existing database. Integrate and combine models such as those from Sklearn PyTorch HuggingFace, with AI APIs like OpenAI, to build even the most complicated AI applications and workflows. With simple Python commands, deploy all your AI models in one environment to automatically compute outputs in your datastore (inference).

KDB.AI, a powerful knowledge based vector database, is a powerful search engine and knowledge-based vector data base that allows developers to create scalable, reliable, and real-time AI applications. It provides advanced search, recommendation, and personalization. Vector databases are the next generation of data management, designed for applications such as generative AI, IoT or time series. Here's what makes them unique, how they work and the new applications they're designed to serve.

The enterprise database for time series, documents, and vectors. Store any type data and combine the simplicity and scalability NoSQL with SQL. CrateDB is a distributed database that runs queries in milliseconds regardless of the complexity, volume, and velocity.

Vald is a distributed, fast, dense and highly scalable vector search engine that approximates nearest neighbors. Vald was designed and implemented using the Cloud-Native architecture. It uses the fastest ANN Algorithm NGT for searching neighbors. Vald supports automatic vector indexing, index backup, horizontal scaling, which allows you to search from billions upon billions of feature vector data. Vald is simple to use, rich in features, and highly customizable. Usually, the graph must be locked during indexing. This can cause stop-the world. Vald uses distributed index graphs so that it continues to work while indexing. Vald has its own highly customizable Ingress/Egress filter. This can be configured to work with the gRPC interface. Horizontal scaling is available on memory and cpu according to your needs. Vald supports disaster recovery by enabling auto backup using Persistent Volume or Object Storage.

In less than 2 minutes, you can create a backend. Get a Postgres database, authentication and instant APIs to start your project. Real-time subscriptions are also available. You can build faster and concentrate on your products. Every project is a Postgres database, the most trusted relational database in the world. You can add user sign-ups or logins to secure your data with Row Level Security. Large files can be stored, organized and served. Any media, including images and videos. Without the need to deploy or scale servers, you can write custom code and cron jobs. There are many starter projects and example apps to help you get started. We will instantly inspect your database and provide APIs. Stop creating repetitive CRUD endpoints. Instead, focus on your product. Type definitions directly from your database schema. Supabase can be used in the browser without a build. You can develop locally and push to production as soon as you are ready. You can manage Supabase projects on your local machine.

Use user feedback and semantic relevance to reliably retrieve optimal document chunks for your retrieval-augmented generation system. In your search system, combine semantic relevance with document freshness because recent results are more accurate. Create a personalized ecommerce feed in real-time using user vectors based on the SKU embeddings that were viewed by the user. A vector index in your warehouse can be used to discover behavioral clusters among your customers. Use spaces to build your indices, and run queries all within a Python Notebook.

Atlas integrates with your workflow by organizing text, embedding datasets and creating interactive maps that can be explored in a web browser. To understand your data, you don't need to scroll through Excel files or log Dataframes. Atlas automatically analyzes, organizes, and summarizes your documents, surfacing patterns and trends. Atlas' pre-organized data interface makes it easy to quickly identify and remove any data that could be harmful to your AI projects. You can label and tag your data, while cleaning it up with instant sync to your Jupyter notebook. Although vector databases are powerful, they can be difficult to interpret. Atlas stores, visualizes, and allows you to search through all your vectors within the same API.

If you are one of the many organizations migrating a commercial database to open source, such as MySQL and PostgreSQL or if your company is building new applications using open-source database management system (OSDBMS), you will know that there is no commercial tooling available for these databases. Imagine if you could save money and be able to quickly ramp up your business using a familiar tool set. Toad Edge® makes it possible. It's a lightweight and reliable desktop tool that simplifies the development and management of open-source databases. Toad for MySQL or PostgreSQL management makes learning new databases easy. Toad Edge is a great tool for MariaDB, Amazon Redshift, and EDB Postgres Advanced Server. Toad Edge supports coding and editing, schema compare, sync, and DevOps CI processes so that you can manage open-source databases quickly and confidently.

Semantee, a managed database that is easy to configure and optimized for semantic searches, is hassle-free. It is available as a set REST APIs that can be easily integrated into any application in minutes. It offers multilingual semantic searching for applications of any size, both on-premise and in the cloud. The product is significantly cheaper and more transparent than most providers, and is optimized for large-scale applications. Semantee also offers an abstraction layer over an e-shop's product catalog, enabling the store to utilize semantic search instantly without having to re-configure its database.

Greenplum Database®, an open-source data warehouse, is a fully featured, advanced, and fully functional data warehouse. It offers powerful and fast analytics on petabyte-scale data volumes. Greenplum Database is uniquely designed for big data analytics. It is powered by the most advanced cost-based query optimizer in the world, delivering high analytical query performance with large data volumes. The Apache 2 license is used to release Greenplum Database®. We would like to thank all of our community contributors. We are also open to new contributions. We encourage all contributions to the Greenplum Database community, no matter how small. Open-source, massively parallel data platform for machine learning, analytics, and AI. Rapidly create and deploy models to support complex applications in cybersecurity, predictive management, risk management, fraud detection, among other areas. The fully integrated, open-source analytics platform is now available.

FoundationDB supports multiple models, so you can store different types of data in one database. All data can be safely stored, distributed and replicated in Key-Value Store. FoundationDB is easy-to-use, grow, and maintain. It uses a distributed architecture that scales out gracefully and handles faults, while acting as a single ACID database. FoundationDB is extremely fast on commodity hardware and can support very heavy loads at a low cost. FoundationDB has been in production for many years and has learned from its mistakes. FoundationDB is supported by an unmatched testing system that is based on a deterministic simulator engine.

TimescaleDB is the most popular open-source relational database that supports time-series data. Fully managed or self-hosted. You can rely on the same PostgreSQL that you love. It has full SQL, rock-solid reliability and a huge ecosystem. Write millions of data points per node. Horizontally scale up to petabytes. Don't worry too much about cardinality. Reduce complexity, ask more questions and build more powerful applications. You will save money with 94-97% compression rates using best-in-class algorithms, and other performance improvements. Modern cloud-native relational database platform that stores time-series data. It is based on PostgreSQL and TimescaleDB. This is the fastest, easiest, and most reliable way to store all of your time-series information. All observability data can be considered time-series data. Time-series problems are those that require efficient solutions to infrastructure and application problems.

You need to connect your proprietary database with the most popular database tools such as Access, Visual Basic and PowerBuilder. The Dr. DeeBee®, ODBC Driver kit makes it easy! Dr. DeeBee ODBC Driver Kit makes it easy to create ODBC database driver drivers quickly and easily. This ODBC tool lets you ODBC enable any database. It allows you to add database connectivity to any proprietary databases without having to know all the complexities of ODBC. Dr. DeeBee ODBC Driver Kit includes the complete source code to create a fully functional ODBC driver you can modify and distribute without any restrictions. You only need to implement OpenTable, NextRecord and GetData calls, then recompile your driver. It's that easy! The Network Edition contains all the source code for a fully functional, "network enabled", Level 2 (most), ODBC3.0 driver that you can modify or distribute royalty-free.

Amazon MSK is a fully managed service that makes coding and running applications that use Apache Kafka for streaming data processing easy. Apache Kafka is an open source platform that allows you to build real-time streaming data applications and pipelines. Amazon MSK allows you to use native Apache Kafka APIs for populating data lakes, stream changes between databases, and to power machine learning or analytics applications. It is difficult to set up, scale, and manage Apache Kafka clusters in production. Apache Kafka clusters can be difficult to set up and scale on your own.

We are glad you are here! BergDB is a Java/.NET database that is simple and efficient. It was designed for developers who want to concentrate on their specific task and not waste time worrying about database issues. BergDB features include simple key-value storage and ACID transactions, historical queries, efficient concurrency controls, secondary indexes with fast append-only storage, replication, transparent object Serialization, and more. BergDB is an embedded, NoSQL, open-source, schemaless, document-oriented, NoSQL, embedded database. BergDB was built from the ground up to execute transactions extremely quickly. There are no compromises. All writes to the database are done in ACID transactions with the highest level of consistency (in SQL-speak, serializable isolation). Historical queries are useful when there are previous data states that are relevant. They also serve as a quick way to manage concurrency. BergDB does not lock anything when a read operation is performed.

Answer questions today, not next week. Latitude makes it easy to create low-code data apps within minutes. You don't need a data stack, but you can help your team answer data-related questions. Connect your data sources to Latitude and you can immediately start exploring your data. Latitude connects with your database, data warehouse, or other tools used by your team. Multiple sources can be used in the same analysis. We support over 100 data sources. Latitude offers a vast array of data sources that can be used by teams to explore and transform data. This includes using our AI SQL Assistant, visual programming, and manually writing SQL queries. Latitude combines data exploration with visualization. You can choose from tables or charts and add them to the canvas you are currently working on. Interactive views are easy to create because your canvas already knows how variables and transformations work together.

Easy deployment of applications to the cloud with your choice in languages and frameworks. High availability and elastic scaling are built-in features that help you achieve business continuity and respond dynamically to changes in customer demands. Azure IP Advantage provides unparalleled security and compliance. The global network of Microsoft's data centers also offers industry-leading reach. No hidden costs. Choose the right resources to meet your workloads. Combining MariaDB Community Edition with the benefits of an entirely managed service provider will free developers from complex database management and infrastructure so they can concentrate on building exceptional applications. Azure Database for MariaDB integrates tightly with Azure web applications and works with popular open source frameworks and languages. Use it with popular content-management apps, such as WordPress or Drupal, to get a fully integrated solution that supports your application development needs.

Percona Server is a free, open-source replacement for MongoDB Community Edition. It combines all of the features and benefits from MongoDB Community Edition with enterprise-class Percona features. Percona Server is based on MongoDB Community Edition and offers flexible data structure, native high-availability, easy scalability, developer-friendly syntax, and a flexible data structure. It also features an in-memory engine and hot backups, LDAP authentication and database auditing.

Directus is an Open Data Platform that allows you to manage any SQL database's content. It offers a powerful API layer to developers and an intuitive app for non-technical users. Directus is written entirely in JavaScript (primarily Node.js or Vue.js), and it is modular and extensible. This allows it to be tailored to your specific project needs. Our platform can be used to manage digital experiences as a headless CMS, a database client for democratizing information, or as a standalone web app for back-office CRM, inventory, business intelligence and project management.

All your ELT data pipelines, including custom ones, will be up and running in minutes. Your team can focus on innovation and insights. Unify all your data integration pipelines with one open-source ELT platform. Airbyte can meet all the connector needs of your data team, no matter how complex or large they may be. Airbyte is a data integration platform that scales to meet your high-volume or custom needs. From large databases to the long tail API sources. Airbyte offers a long list of connectors with high quality that can adapt to API and schema changes. It is possible to unify all native and custom ELT. Our connector development kit allows you to quickly edit and create new connectors from pre-built open-source ones. Transparent and scalable pricing. Finally, transparent and predictable pricing that scales with data needs. No need to worry about volume. No need to create custom systems for your internal scripts or database replication.

Aiven manages your open-source data infrastructure in the cloud so that you don't have. Developers can do what is best for them: create applications. We do what we love: manage cloud data infrastructure. All solutions are open-source. You can also freely transfer data between clouds and create multi-cloud environments. You will know exactly what you will be paying and why. We combine storage, networking, and basic support costs. We will keep your Aiven software up and running. We will be there to help you if there is ever an issue. In 10 minutes, you can deploy a service on Aiven. 1. Register now - No credit card information required 2. Select your open-source service and choose the region and cloud to deploy to it 3. Select your plan and get $300 in credit 4. Click "Create service" to configure your data sources

Baserow is the open-source platform that empowers you to build scalable databases and applications without code. It supports real-time collaboration, workflow automation, and streamlined data management. • User-friendly interface: With Baserow, you don't need to be a tech wizard to create powerful databases. Its intuitive drag-and-drop interface makes it a breeze for anyone on your team to design, customize, and manage data without any hassle. • Collaboration: Multiple users can work on the same database in real-time, ensuring everyone's always on the same page. Share your progress with teammates, assign tasks, and watch your projects flourish. • Fully customizable: Your team is unique, and your database should be too. Tailor every aspect of your database to fit your specific needs. From custom fields to personalized views, Baserow gives you the freedom to build a database that's as individual as your team. • Open source advantage: Being open source means Baserow is continuously improving with contributions from its community. You get a reliable, secure platform that grows with you, plus the flexibility to modify it as you see fit. This includes having no vendor lock-in, which is critical for business continuity.

Navicat Data Modeller is a powerful, cost-effective database design tool that helps you create high-quality conceptual and logical data models. It can be used to create database structures, reverse/forward engineer processes, import models directly from ODBC data sources, create complex SQL/DDL, and print models to files. It makes it easy to create complex entity relationship models. You can also generate script SQL in just one click. Navicat Data Modeler supports many database systems including MySQL, MariaDB and Oracle, SQL Servers, PostgreSQL and SQLite. Professional object designers are available for Tables or Views. They can help you create, modify, and design models. You'll always know what you are doing, even if you don't need to write complex SQL. Navicat Data Modeler also supports three standard notations: Crow's Foot (IDEF1x), UML (Unified Modeling Language) and UML.

GeoSpock DB - The space-time analytics database - allows data fusion in the connected world. GeoSpockDB is a unique cloud-native database that can be used to query for real-world applications. It can combine multiple sources of Internet of Things data to unlock their full potential, while simultaneously reducing complexity, cost, and complexity. GeoSpock DB enables data fusion and efficient storage. It also allows you to run ANSI SQL query and connect to analytics tools using JDBC/ODBC connectors. Users can perform analysis and share insights with familiar toolsets. This includes support for common BI tools such as Tableau™, Amazon QuickSight™, and Microsoft Power BI™, as well as Data Science and Machine Learning environments (including Python Notebooks or Apache Spark). The database can be integrated with internal applications as well as web services, including compatibility with open-source visualisation libraries like Cesium.js and Kepler.

Tatsoft's FactoryStudio provides the tools you need to quickly design secure and powerful industrial applications. Features include real-time data modeling and data logging, MQTT client/spB broker/spB, audit trails, alarms & incidents, visual SQL query gateway, high-performance smart screens, HTML5 dashboards. WPF drawing tools. iOS app, trends, annotations, reporting & much more! Programming scripts can be done in C#, VB.NET or JavaScript. You can get up and running in no time with ZERO client install and just 2 minutes server side installation. It includes many native protocol drivers for PLCs, DCSs, as well as support for other industry standards like OPC, MQTT, and more. Are you looking for a driver that we don't yet have? We also have a toolkit to help you develop protocol drivers! FactoryStudio is your data hub for your industrial ecosystem. It can be your link between IT, OT, real-time devices and your SQL data sources.

BigLake is a storage platform that unifies data warehouses, lakes and allows BigQuery and open-source frameworks such as Spark to access data with fine-grained control. BigLake offers accelerated query performance across multicloud storage and open formats like Apache Iceberg. You can store one copy of your data across all data warehouses and lakes. Multi-cloud governance and fine-grained access control for distributed data. Integration with open-source analytics tools, and open data formats is seamless. You can unlock analytics on distributed data no matter where it is stored. While choosing the best open-source or cloud-native analytics tools over a single copy, you can also access analytics on distributed data. Fine-grained access control for open source engines such as Apache Spark, Presto and Trino and open formats like Parquet. BigQuery supports performant queries on data lakes. Integrates with Dataplex for management at scale, including logical organization.

This is the place where everyone can ask questions and get data-based advice. Get your data connected and in front of your employees. Dashboards, such as this one, are easy to create, share, and examine. Any member of your team can access answers to data questions with just a few clicks. This includes the CEO and Customer Support. SQL and our notebook editor can be used to simplify complex questions. Visual joins, multiple aggregates and filtering steps allow you to dig deeper into your data. To create interactive visualizations that users can modify and explore, you can add variables to your queries. To get the right data to the right people at the right moment, set up alerts or scheduled reports. You can either use the hosted version or Docker to get started on your own. Connect to your existing data and invite your team. You have a BI solution that will take less than a sales call.

Synth is a data-as code tool that offers a simple CLI workflow to generate consistent data in an scalable manner. Synth can be used to generate data that is correct and anonymized, but still looks and sounds like production. Create test data fixtures to support your continuous integration, testing and development. Create data that tells you the story you wish to tell. Specify constraints and relations. Seed development, environments and CI. Anonymize sensitive production data. Create realistic data according to your specifications. Synth's declarative configuration language allows you to specify the entire data model in code. Synth can import existing data and create accurate data models. Synth is database-agnostic and supports semistructured data. It works well with SQL and NoSQL. Synth can generate thousands of semantic types, such as email addresses, credit card numbers and more.

Use CA's Web-enabled, high performance mainframe relational database management software to achieve superior database performance at a low cost and maximum flexibility.

Framework dependent database migration tools can be difficult to set up/configure, and it can be confusing to write migrations. Install Phinx and create your first migration in less than 5 minutes. Phinx can support both PHP and SQL-based migrations. You can use the PHP syntax to make your queries portable between different database vendors. You have the option. Phinx runs from the command-line so it is easy to integrate with your deploy/build or CI tool. Phinx is completely free and open-source software. Developers are encouraged and encouraged to modify, fork, and hack Phinx. If you are using Phinx commercially, please consider making a donation. Purchase the introductory screencast to support Phinx development. Phinx provides extensive documentation.

Peliqan.io provides a data platform that is all-in-one for business teams, IT service providers, startups and scale-ups. No data engineer required. Connect to databases, data warehouses, and SaaS applications. In a spreadsheet interface, you can explore and combine data. Business users can combine multiple data sources, clean data, edit personal copies, and apply transformations. Power users can use SQL on anything, and developers can use Low-code to create interactive data apps, implement writing backs and apply machine intelligence.

RethinkDB sends JSON to your apps instantly. Your app can poll for data but it can be slow, unscalable, and difficult to maintain. RethinkDB is an open-source, scalable database that makes it easy to build realtime apps. Google Docs, Trello and Quora were the first to offer a real-time web experience. RethinkDB makes it easy to create amazing realtime apps with minimal engineering effort. Every player in a multiplayer game must see any changes made by a player. RethinkDB simplifies the data infrastructure to allow for high throughput, low latency realtime interactions. RethinkDB significantly reduces the complexity of creating realtime trading and optimization engine. You can publish real-time updates to thousands and provide pricing updates to clients in milliseconds. RethinkDB data push notifications allow you to create realtime dashboards and make instantaneous business decision.

HeidiSQL is a free program that aims to make it easy to use. "Heidi" allows you to view and edit data and structures on computers that run one of the following database systems: MariaDB, MySQL or Microsoft SQL. Ansgar invented HeidiSQL in 2002. It is one of the most popular tools for MariaDB or MySQL. OpenSource, free for everyone Multiple servers can be connected in one window. MariaDB, MySQL and MS SQL are supported. You can connect to servers via commandline. You can connect via SSH tunnel or SSL settings. Edit tables, views, stored procedures, triggers, and scheduled events. You can create beautiful SQL-exports and then compress them or copy them to the clipboard. Export directly from one server/database to another server/database. You can manage user privileges, import text-files, and export table rows in CSV, HTML HTML, XML, SQL, LaTeX Wiki Markup, and PHP Array. A grid allows you to browse and edit table-data.

Baresquare has a three-part system of action that works with your lifestyle. Our 24/7 anomaly detector tracks site or campaign performance, and uncovers issues before they become a problem. You can get a simple overview of the incident. Now you know why something happened. Baresquare's dashboards alert team leaders with clear, prioritized actions based on the unique needs of your business. The Integrated Knowledge Base records all actions taken, allowing you to streamline workflows, track your progress, and get more out of your data - and your teams. You can promote or demote certain alerts according to your strategy. Finish tasks to teach the system how success looks. We use best-in-class SaaS Standards to support your business requirements securely and at scale. Our technology includes GDPR compliance tools specific to your data policies.

This tutorial series will show you how to use Quadrigram. It will also teach you good practices for data visualization. Quadrigram is an easy-to-use drag and drop tool that allows you to visualize data without any programming. We will be introducing Quadrigram's basic layout to help you get familiar with the tool. The menu bar's left-hand side houses your user profile and the tools for managing your projects. The drop-down menu allows you to create new project, save, rename and share existing projects. You can save your project automatically by clicking the green icon in the right-hand menu. This will ensure that you don't lose any of your work.