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DBMS > Amazon Neptune vs. Lovefield vs. OrigoDB vs. Sphinx vs. Splice Machine

System Properties Comparison Amazon Neptune vs. Lovefield vs. OrigoDB vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonLovefield  Xexclude from comparisonOrigoDB  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudEmbeddable relational database for web apps written in pure JavaScriptA fully ACID in-memory object graph databaseOpen 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 Spark
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument store
Object oriented DBMS
Search engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­neptunegoogle.github.io/­lovefieldorigodb.comsphinxsearch.comsplicemachine.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdorigodb.com/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperAmazonGoogleRobert Friberg et alSphinx Technologies Inc.Splice Machine
Initial release201720142009 infounder the name LiveDB20012014
Current release2.1.12, February 20173.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open SourceOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptC#C++Java
Server operating systemshostedserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesUser defined using .NET types and collectionsnoyes
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 infocan be achieved using .NET
Secondary indexesnoyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like query language infovia JavaScript builder patternnoSQL-like query language (SphinxQL)yes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
.NET Client API
HTTP API
LINQ
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
JavaScript.NetC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesnoyes infoJava
TriggersnoUsing read-only observersyes infoDomain Eventsnoyes
Partitioning methods infoMethods for storing different data on different nodesnonenonehorizontal partitioning infoclient side managed; servers are not synchronizedSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar 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.noneSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesdepending on modelnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infowith encyption-at-restyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes infoWrite ahead logyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing MemoryDByesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noRole based authorizationnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon NeptuneLovefieldOrigoDBSphinxSplice Machine
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