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DBMS > GeoSpock vs. GridGain vs. Milvus vs. Newts vs. RavenDB

System Properties Comparison GeoSpock vs. GridGain vs. Milvus vs. Newts vs. RavenDB

Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonGridGain  Xexclude from comparisonMilvus  Xexclude from comparisonNewts  Xexclude from comparisonRavenDB  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleGridGain is an in-memory computing platform, built on Apache IgniteA DBMS designed for efficient storage of vector data and vector similarity searchesTime Series DBMS based on CassandraOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSKey-value store
Relational DBMS
Vector DBMSTime Series DBMSDocument store
Secondary database modelsTime Series DBMSGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Websitegeospock.comwww.gridgain.commilvus.ioopennms.github.io/­newtsravendb.net
Technical documentationwww.gridgain.com/­docs/­index.htmlmilvus.io/­docs/­overview.mdgithub.com/­OpenNMS/­newts/­wikiravendb.net/­docs
DeveloperGeoSpockGridGain Systems, Inc.OpenNMS GroupHibernating Rhinos
Initial release2007201920142010
Current release2.0, September 2019GridGain 8.5.12.3.4, January 20245.4, July 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
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, JavascriptJava, C++, .NetC++, GoJavaC#
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Linux
macOS
Raspberry Pi
Windows
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringyesno
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.noyesnono
Secondary indexestemporal, categoricalyesnonoyes
SQL infoSupport of SQLANSI SQL for query only (using Presto)ANSI-99 for query and DML statements, subset of DDLnonoSQL-like query language (RQL)
APIs and other access methodsJDBCHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
RESTful HTTP APIHTTP REST
Java API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Java.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)nonoyes
Triggersnoyes (cache interceptors and events)nonoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardingSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)selectable replication factor infobased on CassandraMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)nonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyesyesno
User concepts infoAccess controlAccess rights for users can be defined per tableSecurity Hooks for custom implementationsRole based access control and fine grained access rightsnoAuthorization levels configured per client per database
More information provided by the system vendor
GeoSpockGridGainMilvusNewtsRavenDB
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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GeoSpockGridGainMilvusNewtsRavenDB
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