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DBMS > Amazon Neptune vs. Google Cloud Datastore vs. GridGain vs. OpenEdge vs. Teradata Aster

System Properties Comparison Amazon Neptune vs. Google Cloud Datastore vs. GridGain vs. OpenEdge vs. Teradata Aster

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparisonOpenEdge  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionFast, reliable graph database built for the cloudAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformGridGain is an in-memory computing platform, built on Apache IgniteApplication development environment with integrated database management systemPlatform for big data analytics on multistructured data sources and types
Primary database modelGraph DBMS
RDF store
Document storeKey-value store
Relational DBMS
Relational DBMSRelational 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
Score4.36
Rank#72  Overall
#12  Document stores
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score3.45
Rank#85  Overall
#46  Relational DBMS
Websiteaws.amazon.com/­neptunecloud.google.com/­datastorewww.gridgain.comwww.progress.com/­openedge
Technical documentationaws.amazon.com/­neptune/­developer-resourcescloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.htmldocumentation.progress.com/­output/­ua/­OpenEdge_latest
DeveloperAmazonGoogleGridGain Systems, Inc.Progress Software CorporationTeradata
Initial release20172008200719842005
Current releaseGridGain 8.5.1OpenEdge 12.2, March 2020
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .Net
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
AIX
HP-UX
Linux
Solaris
Windows
Linux
Data schemeschema-freeschema-freeyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes
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.nonoyesyesyes infoin Aster File Store
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLyes infoclose to SQL 92yes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
Progress proprietary ABL (Advanced Business Language)C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnousing Google App Engineyes (compute grid and cache interceptors can be used instead)yesR packages
TriggersnoCallbacks using the Google Apps Engineyes (cache interceptors and events)yesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardinghorizontal 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.Multi-source replication using Paxosyes (replicated cache)Source-replica replicationyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)noyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACID
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.noyesnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsUsers and groupsfine grained access rights according to SQL-standard

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More resources
Amazon NeptuneGoogle Cloud DatastoreGridGainOpenEdgeTeradata Aster
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