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DBMS > BigObject vs. Drizzle vs. EsgynDB vs. Kinetica vs. Milvus

System Properties Comparison BigObject vs. Drizzle vs. EsgynDB vs. Kinetica vs. Milvus

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonDrizzle  Xexclude from comparisonEsgynDB  Xexclude from comparisonKinetica  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.
DescriptionAnalytic DBMS for real-time computations and queriesMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionFully vectorized database across both GPUs and CPUsA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSRelational DBMSRelational DBMSVector DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websitebigobject.iowww.esgyn.cnwww.kinetica.commilvus.io
Technical documentationdocs.bigobject.iodocs.kinetica.commilvus.io/­docs/­overview.md
DeveloperBigObject, Inc.Drizzle project, originally started by Brian AkerEsgynKinetica
Initial release20152008201520122019
Current release7.2.4, September 20127.1, August 20212.3.4, January 2024
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoGNU GPLcommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
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 languageC++C++, JavaC, C++C++, Go
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
FreeBSD
Linux
OS X
LinuxLinuxLinux
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.nononono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith proprietary extensionsyesSQL-like DML and DDL statementsno
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
JDBCADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
All languages supporting JDBC/ODBC/ADO.NetC++
Java
JavaScript (Node.js)
Python
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresLuanoJava Stored Proceduresuser defined functionsno
Triggersnono infohooks for callbacks inside the server can be used.noyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Multi-source replication between multi datacentersSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlnoPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardAccess rights for users and roles on table levelRole based access control and fine grained access rights
More information provided by the system vendor
BigObjectDrizzleEsgynDBKineticaMilvus
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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More resources
BigObjectDrizzleEsgynDBKineticaMilvus
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