DBMS > InfluxDB vs. Microsoft Azure SQL Database vs. Milvus vs. Oracle Berkeley DB vs. PostgreSQL
System Properties Comparison InfluxDB vs. Microsoft Azure SQL Database vs. Milvus vs. Oracle Berkeley DB vs. PostgreSQL
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| Name | InfluxDB Xexclude from comparison | Microsoft Azure SQL Database  formerly SQL Azure Xexclude from comparison | Milvus Xexclude from comparison | Oracle Berkeley DB Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | DBMS for storing time series, events and metrics | Database as a Service offering with high compatibility to Microsoft SQL Server | A DBMS designed for efficient storage of vector data and vector similarity searches | Widely used in-process key-value store | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Time Series DBMS | Relational DBMS | Vector DBMS | Key-value store supports sorted and unsorted key sets Native XML DBMS in the Oracle Berkeley DB XML version | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Spatial DBMS with GEO package | Document store Graph DBMS Spatial DBMS | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.influxdata.com/products/influxdb-overview | azure.microsoft.com/en-us/products/azure-sql/database | milvus.io | www.oracle.com/database/technologies/related/berkeleydb.html | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.influxdata.com/influxdb | docs.microsoft.com/en-us/azure/azure-sql | milvus.io/docs/overview.md | docs.oracle.com/cd/E17076_05/html/index.html | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Microsoft | Oracle originally developed by Sleepycat, which was acquired by Oracle | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2013 | 2010 | 2019 | 1994 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 2.7.6, April 2024 | V12 | 2.4.4, May 2024 | 18.1.40, May 2020 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source MIT-License; commercial enterprise version available | commercial | Open Source Apache Version 2.0 | Open Source commercial license available | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | Zilliz Cloud – Cloud-native service for Milvus |
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| Implementation language | Go | C++ | C++, Go | C, Java, C++ (depending on the Berkeley DB edition) | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux OS X through Homebrew | hosted | Linux macOS 10.14 or laterWindows with WSL 2 enabled | AIX Android FreeBSD iOS Linux OS X Solaris VxWorks Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | yes | schema-free | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | Numeric data and Strings | yes | Vector, Numeric and String | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT. | no | yes | no | yes only with the Berkeley DB XML edition | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | no | yes | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL-like query language | yes | no | yes SQL interfaced based on SQLite is available | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | HTTP API JSON over UDP | ADO.NET JDBC ODBC | RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust Scala | .Net C# Java JavaScript (Node.js) PHP Python Ruby | C++ Go Java JavaScript (Node.js) Python | .Net Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET others Third-party libraries to manipulate Berkeley DB files are available for many languagesC C# C++ Java JavaScript (Node.js) 3rd party bindingPerl Python Tcl | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | Transact SQL | no | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | yes | no | yes only for the SQL API | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding in enterprise version only | Sharding | none | partitioning by range, list and (since PostgreSQL 11) by hash | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | selectable replication factor in enterprise version only | yes, with always 3 replicas available | Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Bounded Staleness Eventual Consistency Immediate Consistency Session Consistency Tunable Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | yes | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID | no | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes Depending on used storage engine | yes | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | simple rights management via user accounts | fine grained access rights according to SQL-standard | Role based access control and fine grained access rights | no | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| InfluxDB | Microsoft Azure SQL Database formerly SQL Azure | Milvus | Oracle Berkeley DB | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | Milvus is an open-source and cloud-native vector database built for production-ready... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | Highly available, versatile, and robust with millisecond latency. Supports batch... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | RAG: retrieval augmented generation Video media : video understanding, video deduplication.... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Market metrics | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | Open source core with closed source clustering available either on-premise or on... » more | Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | Apache Superset and InfluxDB Cloud 3.0 Scaling Data Collection: Solving Renewable Energy Challenges with InfluxDB Deadman Alerts with Grafana and InfluxDB Cloud 3.0 Chasing the Skies: Monitoring Flights with InfluxDB Monitoring Your Cloud Environments and Applications with InfluxDB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| InfluxDB | Microsoft Azure SQL Database formerly SQL Azure | Milvus | Oracle Berkeley DB | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | Why Build a Time Series Data Platform? Time Series DBMS are the database category with the fastest increase in popularity Time Series DBMS as a new trend? | PostgreSQL is the DBMS of the Year 2020 Cloud-based DBMS's popularity grows at high rates The popularity of cloud-based DBMSs has increased tenfold in four years | Vector databases | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services Amazon Timestream: Managed InfluxDB for Time Series Data InfluxData Collaborating with AWS to Bring InfluxDB and Time Series Analytics to Developers Around the World How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency AWS and InfluxData partner to offer managed time series database Timestream for InfluxDB provided by Google News Copilot in Azure SQL Database in Private Preview Microsoft unveils Copilot for Azure SQL Database Azure SQL Database migration to OCI - resources estimation and migration approach Expand the limits of innovation with Azure data Azure SQL Database outage caused by network infrastructure provided by Google News How NVIDIA GPU Acceleration Supercharged Milvus Vector Database AI-Powered Search Engine With Milvus Vector Database on Vultr Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search Zilliz Unveils Game-Changing Features for Vector Search IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI provided by Google News Margo Seltzer Named ACM Athena Lecturer for Technical and Mentoring Contributions ACM recognizes far-reaching technical achievements with special awards Margo I. Seltzer | Berkman Klein Center Oracle buys Sleepycat Software How to store financial market data for backtesting provided by Google News Timescale unveils high-performance AI vector database extensions for PostgreSQL PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions PostgreSQL Tutorial: Definition, Commands, & Features Raise the bar on AI-powered app development with Azure Database for PostgreSQL A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions provided by Google News | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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