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DBMS > BigObject vs. Kinetica vs. Neo4j vs. StarRocks

System Properties Comparison BigObject vs. Kinetica vs. Neo4j vs. StarRocks

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonKinetica  Xexclude from comparisonNeo4j  Xexclude from comparisonStarRocks  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesFully vectorized database across both GPUs and CPUsScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsAn open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics infoForked from Apache Doris
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSGraph DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score44.89
Rank#21  Overall
#1  Graph DBMS
Score0.93
Rank#198  Overall
#93  Relational DBMS
Websitebigobject.iowww.kinetica.comneo4j.comwww.starrocks.io
Technical documentationdocs.bigobject.iodocs.kinetica.comneo4j.com/­docsdocs.starrocks.io/­en-us/­latest/­introduction/­StarRocks_intro
DeveloperBigObject, Inc.KineticaNeo4j, Inc.The Linux Foundation infosince Feb 2023
Initial release2015201220072020
Current release7.1, August 20215.20, May 20243.3, June 2024
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialOpen Source infoGPL version3, commercial licenses availableOpen Source infoApache Version 2.0
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.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageC, C++Java, ScalaC++, Java
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux
Data schemeyesyesschema-free and schema-optionalyes
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.nonono
Secondary indexesyesyesyes infopluggable indexing subsystem, by default Apache Luceneyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsnoyes
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
JDBC
MySQL protocol
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
Java
Server-side scripts infoStored proceduresLuauser defined functionsyes infoUser defined Procedures and Functionsuser defined functions
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infovia event handlerno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes using Neo4j Fabrichorizontal partitioning (by range and hash)
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationCausal 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 systemnoneImmediate Consistency or Eventual Consistency depending on configurationCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Immediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
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.yesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlnoAccess rights for users and roles on table levelUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)Role based access control and fine grained access rights
More information provided by the system vendor
BigObjectKineticaNeo4jStarRocks
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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