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DBMS > Amazon Neptune vs. ObjectBox vs. Splice Machine vs. TerarkDB

System Properties Comparison Amazon Neptune vs. ObjectBox vs. Splice Machine vs. TerarkDB

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonObjectBox  Xexclude from comparisonSplice Machine  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudLightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectorsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelGraph DBMS
RDF store
Object oriented DBMS
Vector DBMS
Relational DBMSKey-value store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score1.08
Rank#179  Overall
#6  Object oriented DBMS
#9  Vector DBMS
Score0.54
Rank#244  Overall
#114  Relational DBMS
Score0.00
Rank#385  Overall
#61  Key-value stores
Websiteaws.amazon.com/­neptunegithub.com/­objectbox
objectbox.io
splicemachine.comgithub.com/­bytedance/­terarkdb
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.objectbox.iosplicemachine.com/­how-it-worksbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperAmazonObjectBox LimitedSplice MachineByteDance, originally Terark
Initial release2017201720142016
Current release4.0 (May 2024)3.1, March 2021
License infoCommercial or Open SourcecommercialBindings are released under Apache 2.0 infoApache License 2.0Open Source infoAGPL 3.0, commercial license availablecommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++JavaC++
Server operating systemshostedAndroid
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyes, plus "flex" map-like typesyesno
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 indexesnoyesyesno
SQL infoSupport of SQLnonoyesno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Proprietary native APIJDBC
Native Spark Datasource
ODBC
C++ API
Java API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnonoyes infoJavano
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnonenoneShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.Data sync between devices allowing occasional connected databases to work completely offlineMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesAccess rights for users, groups and roles according to SQL-standardno
More information provided by the system vendor
Amazon NeptuneObjectBoxSplice MachineTerarkDB
News

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18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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More resources
Amazon NeptuneObjectBoxSplice MachineTerarkDB
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