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DBMS > Amazon Neptune vs. Apache IoTDB vs. GridGain vs. Kinetica vs. OpenEdge

System Properties Comparison Amazon Neptune vs. Apache IoTDB vs. GridGain vs. Kinetica vs. OpenEdge

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGridGain  Xexclude from comparisonKinetica  Xexclude from comparisonOpenEdge  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkGridGain is an in-memory computing platform, built on Apache IgniteFully vectorized database across both GPUs and CPUsApplication development environment with integrated database management system
Primary database modelGraph DBMS
RDF store
Time Series DBMSKey-value store
Relational DBMS
Relational DBMSRelational 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
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score3.45
Rank#85  Overall
#46  Relational DBMS
Websiteaws.amazon.com/­neptuneiotdb.apache.orgwww.gridgain.comwww.kinetica.comwww.progress.com/­openedge
Technical documentationaws.amazon.com/­neptune/­developer-resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.gridgain.com/­docs/­index.htmldocs.kinetica.comdocumentation.progress.com/­output/­ua/­OpenEdge_latest
DeveloperAmazonApache Software FoundationGridGain Systems, Inc.KineticaProgress Software Corporation
Initial release20172018200720121984
Current release1.1.0, April 2023GridGain 8.5.17.1, August 2021OpenEdge 12.2, March 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercialcommercial
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 languageJavaJava, C++, .NetC, C++
Server operating systemshostedAll OS with a Java VM (>= 1.8)Linux
OS X
Solaris
Windows
LinuxAIX
HP-UX
Linux
Solaris
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonoyesnoyes
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoSQL-like query languageANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsyes infoclose to SQL 92
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
Native API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Progress proprietary ABL (Advanced Business Language)
Server-side scripts infoStored proceduresnoyesyes (compute grid and cache interceptors can be used instead)user defined functionsyes
Triggersnoyesyes (cache interceptors and events)yes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardinghorizontal partitioning infosince Version 11.4
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.selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes (replicated cache)Source-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparkyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
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.yesyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesSecurity Hooks for custom implementationsAccess rights for users and roles on table levelUsers and groups

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More resources
Amazon NeptuneApache IoTDBGridGainKineticaOpenEdge
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