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DBMS > Datomic vs. Drizzle vs. Hive vs. Microsoft Azure Synapse Analytics vs. Milvus

System Properties Comparison Datomic vs. Drizzle vs. Hive vs. Microsoft Azure Synapse Analytics vs. Milvus

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonDrizzle  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMilvus  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.data warehouse software for querying and managing large distributed datasets, built on HadoopElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score22.71
Rank#30  Overall
#18  Relational DBMS
Score1.81
Rank#144  Overall
#5  Vector DBMS
Websitewww.datomic.comhive.apache.orgazure.microsoft.com/­services/­synapse-analyticsmilvus.io
Technical documentationdocs.datomic.comcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­azure/­synapse-analyticsmilvus.io/­docs/­overview.md
DeveloperCognitectDrizzle project, originally started by Brian AkerApache Software Foundation infoinitially developed by FacebookMicrosoft
Initial release20122008201220162019
Current release1.0.6735, June 20237.2.4, September 20123.1.3, April 20222.3.4, January 2024
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoGNU GPLOpen Source infoApache Version 2commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageJava, ClojureC++JavaC++C++, Go
Server operating systemsAll OS with a Java VMFreeBSD
Linux
OS X
All OS with a Java VMhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesVector, Numeric and String
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLnoyes infowith proprietary extensionsSQL-like DML and DDL statementsyesno
APIs and other access methodsRESTful HTTP APIJDBCJDBC
ODBC
Thrift
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
Java
C
C++
Java
PHP
C++
Java
PHP
Python
C#
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyes infouser defined functions and integration of map-reduceTransact SQLno
TriggersBy using transaction functionsno infohooks for callbacks inside the server can be used.nonono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
selectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyesnono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyes
User concepts infoAccess controlnoPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and rolesyesRole based access control and fine grained access rights
More information provided by the system vendor
DatomicDrizzleHiveMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvus
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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DatomicDrizzleHiveMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvus
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