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DBMS > eXtremeDB vs. Geode vs. Milvus vs. Spark SQL

System Properties Comparison eXtremeDB vs. Geode vs. Milvus vs. Spark SQL

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Editorial information provided by DB-Engines
NameeXtremeDB  Xexclude from comparisonGeode  Xexclude from comparisonMilvus  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionNatively in-memory DBMS with options for persistency, high-availability and clusteringGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesA DBMS designed for efficient storage of vector data and vector similarity searchesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeVector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score1.86
Rank#134  Overall
#24  Key-value stores
Score2.78
Rank#103  Overall
#4  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.mcobject.comgeode.apache.orgmilvus.iospark.apache.org/­sql
Technical documentationwww.mcobject.com/­docs/­extremedb.htmgeode.apache.org/­docsmilvus.io/­docs/­overview.mdspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMcObjectOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Apache Software Foundation
Initial release2001200220192014
Current release8.2, 20211.1, February 20172.4.4, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC and C++JavaC++, GoScala
Server operating systemsAIX
HP-UX
Linux
macOS
Solaris
Windows
All OS with a Java VM infothe JDK (8 or later) is also requiredLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringyes
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.no infosupport of XML interfaces availablenonono
Secondary indexesyesnonono
SQL infoSupport of SQLyes infowith the option: eXtremeSQLSQL-like query language (OQL)noSQL-like DML and DDL statements
APIs and other access methods.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
Java Client API
Memcached protocol
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
.Net
All JVM based languages
C++
Groovy
Java
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functionsnono
Triggersyes infoby defining eventsyes infoCache Event Listenersnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Multi-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodenono
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlAccess rights per client and object definableRole based access control and fine grained access rightsno
More information provided by the system vendor
eXtremeDBGeodeMilvusSpark SQL
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Milvus is an open-source and cloud-native vector database built for production-ready...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Highly available, versatile, and robust with millisecond latency. Supports batch...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
As of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more
Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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More resources
eXtremeDBGeodeMilvusSpark SQL
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