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DBMS > Amazon Neptune vs. GigaSpaces vs. Lovefield vs. Splice Machine

System Properties Comparison Amazon Neptune vs. GigaSpaces vs. Lovefield vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGigaSpaces  Xexclude from comparisonLovefield  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsEmbeddable relational database for web apps written in pure JavaScriptOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelGraph DBMS
RDF store
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­neptunewww.gigaspaces.comgoogle.github.io/­lovefieldsplicemachine.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.gigaspaces.com/­latest/­landing.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsplicemachine.com/­how-it-works
DeveloperAmazonGigaspaces TechnologiesGoogleSplice Machine
Initial release2017200020142014
Current release15.5, September 20202.1.12, February 20173.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJavaScriptJava
Server operating systemshostedLinux
macOS
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
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.nono infoXML can be used for describing objects metadatano
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoSQL-99 for query and DML statementsSQL-like query language infovia JavaScript builder patternyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C++
Java
Python
Scala
JavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnoyes infoJava
Triggersnoyes, event driven architectureUsing read-only observersyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneShared 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.Multi-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing MemoryDByes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Role-based access controlnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon NeptuneGigaSpacesLovefieldSplice Machine
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