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DBMS > Amazon Neptune vs. Datomic vs. Hypertable vs. Kinetica

System Properties Comparison Amazon Neptune vs. Datomic vs. Hypertable vs. Kinetica

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDatomic  Xexclude from comparisonHypertable  Xexclude from comparisonKinetica  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionFast, reliable graph database built for the cloudDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAn open source BigTable implementation based on distributed file systems such as HadoopFully vectorized database across both GPUs and CPUs
Primary database modelGraph DBMS
RDF store
Relational DBMSWide column storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series 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
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websiteaws.amazon.com/­neptunewww.datomic.comwww.kinetica.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.datomic.comdocs.kinetica.com
DeveloperAmazonCognitectHypertable Inc.Kinetica
Initial release2017201220092012
Current release1.0.7075, December 20230.9.8.11, March 20167.1, August 2021
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoGNU version 3. Commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++C, C++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Windows infoan inofficial Windows port is available
Linux
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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
Secondary indexesnoyesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLnononoSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
RESTful HTTP APIC++ API
Thrift
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Clojure
Java
C++
Java
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsnouser defined functions
TriggersnoBy using transaction functionsnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShardingSharding
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.none infoBut extensive use of caching in the application peersselectable replication factor on file system levelSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)nonoAccess rights for users and roles on table level

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More resources
Amazon NeptuneDatomicHypertableKinetica
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