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DBMS > Citus vs. Drizzle vs. GeoSpock vs. Neo4j

System Properties Comparison Citus vs. Drizzle vs. GeoSpock vs. Neo4j

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDrizzle  Xexclude from comparisonGeoSpock  Xexclude from comparisonNeo4j  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.GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Spatial and temporal data processing engine for extreme data scaleScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings
Primary database modelRelational DBMSRelational DBMSRelational DBMSGraph DBMS
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score44.46
Rank#23  Overall
#1  Graph DBMS
Websitewww.citusdata.comgeospock.comneo4j.com
Technical documentationdocs.citusdata.comneo4j.com/­docs
DeveloperDrizzle project, originally started by Brian AkerGeoSpockNeo4j, Inc.
Initial release201020082007
Current release8.1, December 20187.2.4, September 20122.0, September 20195.19, April 2024
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoGNU GPLcommercialOpen Source infoGPL version3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageCC++Java, JavascriptJava, Scala
Server operating systemsLinuxFreeBSD
Linux
OS X
hostedLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Data schemeyesyesyesschema-free and schema-optional
Typing infopredefined data types such as float or dateyesyesyesyes
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.yes infospecific XML type available, but no XML query functionalityno
Secondary indexesyesyestemporal, categoricalyes infopluggable indexing subsystem, by default Apache Lucene
SQL infoSupport of SQLyes infostandard, with numerous extensionsyes infowith proprietary extensionsANSI SQL for query only (using Presto)no
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBCJDBCBolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Java
PHP
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nonoyes infoUser defined Procedures and Functions
Triggersyesno infohooks for callbacks inside the server can be used.noyes infovia event handler
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic shardingyes using Neo4j Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
Causal Clustering using Raft protocol infoavailable in in Enterprise Version only
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Foreign keys infoReferential integrityyesyesnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users can be defined per tableUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)
More information provided by the system vendor
CitusDrizzleGeoSpockNeo4j
Specific characteristicsNeo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
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