DBMS > EDB Postgres vs. Elasticsearch vs. Microsoft Azure Data Explorer vs. Milvus vs. SingleStore
System Properties Comparison EDB Postgres vs. Elasticsearch vs. Microsoft Azure Data Explorer vs. Milvus vs. SingleStore
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Name | EDB Postgres Xexclude from comparison | Elasticsearch Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Milvus Xexclude from comparison | SingleStore former name was MemSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration. | A distributed, RESTful modern search and analytics engine based on Apache Lucene Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric | Fully managed big data interactive analytics platform | A DBMS designed for efficient storage of vector data and vector similarity searches | MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Search engine | Relational DBMS column oriented | Vector DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store Spatial DBMS | Document store Spatial DBMS Vector DBMS | Document store If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell Event Store this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps) Spatial DBMS Search engine support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine Time Series DBMS see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Document store Spatial DBMS Time Series DBMS Vector DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.enterprisedb.com | www.elastic.co/elasticsearch | azure.microsoft.com/services/data-explorer | milvus.io | www.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | www.enterprisedb.com/docs | www.elastic.co/guide/en/elasticsearch/reference/current/index.html | docs.microsoft.com/en-us/azure/data-explorer | milvus.io/docs/overview.md | docs.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | EnterpriseDB | Elastic | Microsoft | SingleStore Inc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2005 | 2010 | 2019 | 2019 | 2013 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 14, December 2021 | 8.6, January 2023 | cloud service with continuous releases | 2.3.4, January 2024 | 8.5, January 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial BSD for PostgreSQL-components | Open Source Elastic License | commercial | Open Source Apache Version 2.0 | commercial free developer edition available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | yes | 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 | SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C | Java | C++, Go | C++, Go | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux Windows | All OS with a Java VM | hosted | Linux macOS 10.14 or later Windows with WSL 2 enabled | Linux 64 bit version required | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | schema-free Flexible type definitions. Once a type is defined, it is persistent | Fixed schema with schema-less datatypes (dynamic) | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | Vector, Numeric and String | 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. | yes specific XML-type available, but no XML query functionality. | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes All search fields are automatically indexed | all fields are automatically indexed | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes standard with numerous extensions | SQL-like query language | Kusto Query Language (KQL), SQL subset | no | yes but no triggers and foreign keys | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | ADO.NET JDBC native C library ODBC streaming API for large objects | Java API RESTful HTTP/JSON API | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | RESTful HTTP API | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C C++ Delphi Java Perl PHP Python Tcl | .Net Groovy Community Contributed Clients Java JavaScript Perl PHP Python Ruby | .Net Go Java JavaScript (Node.js) PowerShell Python R | C++ Go Java JavaScript (Node.js) Python | Bash C C# Java JavaScript (Node.js) Python | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | yes | Yes, possible languages: KQL, Python, R | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | yes by using the 'percolation' feature | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | horizontal partitioning by hash, list or range | Sharding | Sharding Implicit feature of the cloud service | Sharding | Sharding hash partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication | yes | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Source-replica replication stores two copies of each physical data partition on two separate nodes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | ES-Hadoop Connector | Spark connector (open source): github.com/Azure/azure-kusto-spark | no | no can define user-defined aggregate functions for map-reduce-style calculations | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual Consistency Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all | Eventual Consistency Immediate Consistency | Bounded Staleness Eventual Consistency Immediate Consistency Session Consistency Tunable Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | no | no | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes, multi-version concurrency control (MVCC) | yes | yes | yes | yes, multi-version concurrency control (MVCC) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | Memcached and Redis integration | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | fine grained access rights according to SQL-standard | Azure Active Directory Authentication | Role based access control and fine grained access rights | Fine grained access control via users, groups and roles | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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EDB Postgres | Elasticsearch | Microsoft Azure Data Explorer | Milvus | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Milvus is an open-source and cloud-native vector database built for production-ready... » more | SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Highly available, versatile, and robust with millisecond latency. Supports batch... » more | SingleStore’s competitive advantages include: Easy and Simplified Architecture with... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | RAG: retrieval augmented generation Video media : video understanding, video deduplication.... » more | Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,... » more | IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise... » more | Customers in various industries worldwide including US and International Industry... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed... » more | F ree Tier and Enterprise Edition » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
EDB Postgres | Elasticsearch | Microsoft Azure Data Explorer | Milvus | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | PostgreSQL is the DBMS of the Year 2017 Elasticsearch moved into the top 10 most popular database management systems MySQL, PostgreSQL and Redis are the winners of the March ranking | Vector databases | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems EDB unveils EDB Postgres AI EDB Puts Postgres in the Middle of Analytics Workflow with New Lakehouse Stack EDB Announces EDB Postgres® AI, an Intelligent Platform for Transactional, Analytical and AI Workloads Nutanix partners with EDB to fit database service for AI – Blocks and Files EDB Postgres AI is a new platform for analytics workloads provided by Google News Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB? 8 Powerful Alternatives to Elasticsearch AI security challenges in generative AI adoption Splunk vs Elasticsearch | A Comparison and How to Choose Introducing Elasticsearch Vector Database to Azure OpenAI Service On Your Data (Preview) provided by Google News We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates Update records in a Kusto Database (public preview) | Azure updates Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints ... New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates 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 Building a Modern Database: Nikita Shamgunov on Postgres and Beyond SingleStore CEO sees little future for purpose-built vector databases SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development SingleStore, Snowflake Help Customers Build Enterprise-Ready Generative AI Apps Announcing watsonx.ai and SingleStore for generative AI applications provided by Google News |
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