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

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

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonBrytlyt  Xexclude from comparisonGigaSpaces  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsOpen-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 infoValues are user defined objects
Relational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.27
Rank#292  Overall
#132  Relational DBMS
Score0.91
Rank#197  Overall
#33  Document stores
#7  Object oriented DBMS
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­neptunebrytlyt.iowww.gigaspaces.comsplicemachine.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.brytlyt.iodocs.gigaspaces.com/­latest/­landing.htmlsplicemachine.com/­how-it-works
DeveloperAmazonBrytlytGigaspaces TechnologiesSplice Machine
Initial release2017201620002014
Current release5.0, August 202315.5, September 20203.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; Commercial licenses availableOpen 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 languageC, C++ and CUDAJava, C++, .NetJava
Server operating systemshostedLinux
OS X
Windows
Linux
macOS
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes
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.noyes infospecific XML-type available, but no XML query functionality.no infoXML can be used for describing objects metadata
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyesSQL-99 for query and DML statementsyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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
C++
Delphi
Java
Perl
Python
Tcl
.Net
C++
Java
Python
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions infoin PL/pgSQLyesyes infoJava
Triggersnoyesyes, event driven architectureyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShared 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.Source-replica replicationMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoMap-Reduce pattern can be built with XAP task executorsYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnoyes
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-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardRole-based access controlAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon NeptuneBrytlytGigaSpacesSplice Machine
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