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DBMS > Amazon Neptune vs. AnzoGraph DB vs. HEAVY.AI vs. jBASE vs. Kinetica

System Properties Comparison Amazon Neptune vs. AnzoGraph DB vs. HEAVY.AI vs. jBASE vs. Kinetica

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonAnzoGraph DB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonjBASE  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA robust multi-value DBMS comprising development tools and middlewareFully vectorized database across both GPUs and CPUs
Primary database modelGraph DBMS
RDF store
Graph DBMS
RDF store
Relational DBMSMultivalue DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score1.41
Rank#159  Overall
#3  Multivalue DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteaws.amazon.com/­neptunecambridgesemantics.com/­anzographgithub.com/­heavyai/­heavydb
www.heavy.ai
www.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.kinetica.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.heavy.aidocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.kinetica.com
DeveloperAmazonCambridge SemanticsHEAVY.AI, Inc.Rocket Software (formerly Zumasys)Kinetica
Initial release20172018201619912012
Current release2.3, January 20215.10, January 20225.77.1, August 2021
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availableOpen Source infoApache Version 2; enterprise edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAC, C++
Server operating systemshostedLinuxLinuxAIX
Linux
Windows
Linux
Data schemeschema-freeSchema-free and OWL/RDFS-schema supportyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesoptionalyes
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.nononoyesno
Secondary indexesnononoyes
SQL infoSupport of SQLnoSPARQL and SPARQL* as primary query language. Cypher preview.yesEmbedded SQL for jBASE in BASICSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C++
Java
Python
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Basic
Jabbascript
Java
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnoyesuser defined functions
Triggersnononoyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic shardingSharding infoRound robinShardingSharding
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 in MPP-ClusterMulti-source replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoKerberos/HDFS data loadingnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in MPP-ClusterImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoRelationships in graphsno infonot needed in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes 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)Access rights for users and rolesfine grained access rights according to SQL-standardAccess rights can be defined down to the item levelAccess rights for users and roles on table level

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More resources
Amazon NeptuneAnzoGraph DBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022jBASEKinetica
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