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DBMS > Amazon Neptune vs. Graph Engine vs. OpenEdge vs. ReductStore vs. Splice Machine

System Properties Comparison Amazon Neptune vs. Graph Engine vs. OpenEdge vs. ReductStore vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonOpenEdge  Xexclude from comparisonReductStore  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineApplication development environment with integrated database management systemDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.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
Graph DBMS
Key-value store
Relational DBMSTime Series DBMSRelational 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
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score3.51
Rank#86  Overall
#46  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­neptunewww.graphengine.iowww.progress.com/­openedgegithub.com/­reductstore
www.reduct.store
splicemachine.com
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.graphengine.io/­docs/­manualdocumentation.progress.com/­output/­ua/­OpenEdge_latestwww.reduct.store/­docssplicemachine.com/­how-it-works
DeveloperAmazonMicrosoftProgress Software CorporationReductStore LLCSplice Machine
Initial release20172010198420232014
Current releaseOpenEdge 12.2, March 20201.9, March 20243.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicensecommercialOpen Source infoBusiness Source License 1.1Open Source infoAGPL 3.0, commercial license available
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 language.NET and CC++, RustJava
Server operating systemshosted.NETAIX
HP-UX
Linux
Solaris
Windows
Docker
Linux
macOS
Windows
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.nonoyes
Secondary indexesnoyesyes
SQL infoSupport of SQLnonoyes infoclose to SQL 92yes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
RESTful HTTP APIJDBC
ODBC
HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#
C++
F#
Visual Basic
Progress proprietary ABL (Advanced Business Language)C++
JavaScript (Node.js)
Python
Rust
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesyesyes infoJava
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioninghorizontal partitioning infosince Version 11.4Shared 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 replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infowith encyption-at-restoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Users and groupsAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon NeptuneGraph Engine infoformer name: TrinityOpenEdgeReductStoreSplice Machine
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