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DBMS > Cachelot.io vs. Cubrid vs. HugeGraph vs. Milvus vs. Sphinx

System Properties Comparison Cachelot.io vs. Cubrid vs. HugeGraph vs. Milvus vs. Sphinx

Editorial information provided by DB-Engines
NameCachelot.io  Xexclude from comparisonCubrid  Xexclude from comparisonHugeGraph  Xexclude from comparisonMilvus  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionIn-memory caching systemCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPA fast-speed and highly-scalable Graph DBMSA DBMS designed for efficient storage of vector data and vector similarity searchesOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value storeRelational DBMSGraph DBMSVector DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#383  Overall
#60  Key-value stores
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitecachelot.iocubrid.com (korean)
cubrid.org (english)
github.com/­hugegraph
hugegraph.apache.org
milvus.iosphinxsearch.com
Technical documentationcubrid.org/­manualshugegraph.apache.org/­docsmilvus.io/­docs/­overview.mdsphinxsearch.com/­docs
DeveloperCUBRID Corporation, CUBRID FoundationBaiduSphinx Technologies Inc.
Initial release20152008201820192001
Current release11.0, January 20210.92.3.4, January 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoSimplified BSD LicenseOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoGPL version 2, commercial licence available
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, C++, JavaJavaC++, GoC++
Server operating systemsFreeBSD
Linux
OS X
Linux
Windows
Linux
macOS
Unix
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesVector, Numeric and Stringno
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 indexesnoyesyes infoalso supports composite index and range indexnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoyesnonoSQL-like query language (SphinxQL)
APIs and other access methodsMemcached protocolADO.NET
JDBC
ODBC
OLE DB
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP APIProprietary protocol
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Groovy
Java
Python
C++
Go
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoJava Stored Proceduresasynchronous Gremlin script jobsnono
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesnonenoneyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationyes infodepending on used storage backend, e.g. Cassandra and HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonovia hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyesyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentnoyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardUsers, roles and permissionsRole based access control and fine grained access rightsno
More information provided by the system vendor
Cachelot.ioCubridHugeGraphMilvusSphinx
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
Cachelot.ioCubridHugeGraphMilvusSphinx
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