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DBMS > Amazon Neptune vs. Citus vs. Drizzle vs. Splice Machine

System Properties Comparison Amazon Neptune vs. Citus vs. Drizzle vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCitus  Xexclude from comparisonDrizzle  Xexclude from comparisonSplice Machine  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionFast, reliable graph database built for the cloudScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Open-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 DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­neptunewww.citusdata.comsplicemachine.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.citusdata.comsplicemachine.com/­how-it-works
DeveloperAmazonDrizzle project, originally started by Brian AkerSplice Machine
Initial release2017201020082014
Current release8.1, December 20187.2.4, September 20123.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL, commercial license also availableOpen Source infoGNU GPLOpen 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 languageCC++Java
Server operating systemshostedLinuxFreeBSD
Linux
OS X
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
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
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyes infostandard, with numerous extensionsyes infowith proprietary extensionsyes
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
JDBCJDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Java
PHP
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes infoJava
Triggersnoyesno infohooks for callbacks inside the server can be used.yes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShared 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 replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesyesyes
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.noyes
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-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon NeptuneCitusDrizzleSplice Machine
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