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DBMS > Amazon Neptune vs. ObjectBox vs. Sphinx vs. Splice Machine vs. SQream DB

System Properties Comparison Amazon Neptune vs. ObjectBox vs. Sphinx vs. Splice Machine vs. SQream DB

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonObjectBox  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudExtremely fast embedded database for small devices, IoT and MobileOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Sparka GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelGraph DBMS
RDF store
Object oriented DBMSSearch engineRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Websiteaws.amazon.com/­neptuneobjectbox.iosphinxsearch.comsplicemachine.comsqream.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.objectbox.iosphinxsearch.com/­docssplicemachine.com/­how-it-worksdocs.sqream.com
DeveloperAmazonObjectBox LimitedSphinx Technologies Inc.Splice MachineSQream Technologies
Initial release20172017200120142017
Current release3.5.1, February 20233.1, March 20212022.1.6, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache License 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C++JavaC++, CUDA, Haskell, Java, Scala
Server operating systemshostedAndroid
iOS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes, ANSI Standard SQL Types
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.nono
Secondary indexesnoyesyes infofull-text index on all search fieldsyesno
SQL infoSupport of SQLnonoSQL-like query language (SphinxQL)yesyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Proprietary native APIProprietary protocolJDBC
Native Spark Datasource
ODBC
.Net
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnononoyes infoJavauser defined functions in Python
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal and vertical partitioning
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.online/offline synchronization between client and servernoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Amazon NeptuneObjectBoxSphinxSplice MachineSQream DB
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