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DBMS > GridGain vs. MarkLogic vs. Milvus vs. Sphinx

System Properties Comparison GridGain vs. MarkLogic vs. Milvus vs. Sphinx

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonMarkLogic  Xexclude from comparisonMilvus  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteOperational and transactional Enterprise NoSQL databaseA 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 store
Relational DBMS
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Vector DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score2.78
Rank#103  Overall
#4  Vector DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.gridgain.comwww.progress.com/­marklogicmilvus.iosphinxsearch.com
Technical documentationwww.gridgain.com/­docs/­index.htmlwww.progress.com/­marklogic/­documentationmilvus.io/­docs/­overview.mdsphinxsearch.com/­docs
DeveloperGridGain Systems, Inc.MarkLogic Corp.Sphinx Technologies Inc.
Initial release2007200120192001
Current releaseGridGain 8.5.111.0, December 20222.4.4, May 20243.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infoApache Version 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
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, C++, .NetC++C++, GoC++
Server operating systemsLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyesyesVector, 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.yesyesno
Secondary indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLyes infoSQL92noSQL-like query language (SphinxQL)
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
RESTful HTTP APIProprietary protocol
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
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 proceduresyes (compute grid and cache interceptors can be used instead)yes infovia XQuery or JavaScriptnono
Triggersyes (cache interceptors and events)yesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)yes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infocan act as a resource manager in an XA/JTA transactionnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yesyes, with Range Indexesyes
User concepts infoAccess controlSecurity Hooks for custom implementationsRole-based access control at the document and subdocument levelsRole based access control and fine grained access rightsno
More information provided by the system vendor
GridGainMarkLogicMilvusSphinx
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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