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

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

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGridGain  Xexclude from comparisonOpenEdge  Xexclude from comparisonPrometheus  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 IgniteApplication development environment with integrated database management systemOpen-source Time Series DBMS and monitoring system
Primary database modelGraph DBMS
RDF store
Time Series DBMSKey-value store
Relational DBMS
Relational DBMSTime 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
Score3.45
Rank#85  Overall
#46  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websiteaws.amazon.com/­neptuneiotdb.apache.orgwww.gridgain.comwww.progress.com/­openedgeprometheus.io
Technical documentationaws.amazon.com/­neptune/­developer-resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.gridgain.com/­docs/­index.htmldocumentation.progress.com/­output/­ua/­OpenEdge_latestprometheus.io/­docs
DeveloperAmazonApache Software FoundationGridGain Systems, Inc.Progress Software Corporation
Initial release20172018200719842015
Current release1.1.0, April 2023GridGain 8.5.1OpenEdge 12.2, March 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0
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++, .NetGo
Server operating systemshostedAll OS with a Java VM (>= 1.8)Linux
OS X
Solaris
Windows
AIX
HP-UX
Linux
Solaris
Windows
Linux
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesNumeric data only
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.nonoyesyesno infoImport of XML data possible
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnoSQL-like query languageANSI-99 for query and DML statements, subset of DDLyes infoclose to SQL 92no
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/JSON API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
Progress proprietary ABL (Advanced Business Language).Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresnoyesyes (compute grid and cache interceptors can be used instead)yesno
Triggersnoyesyes (cache interceptors and events)yesno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioning infosince Version 11.4Sharding
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 replicationyes infoby Federation
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 Consistencynone
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDno
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.yesyesnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesSecurity Hooks for custom implementationsUsers and groupsno

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More resources
Amazon NeptuneApache IoTDBGridGainOpenEdgePrometheus
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