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DBMS > Amazon Neptune vs. GigaSpaces vs. Google Cloud Datastore vs. OpenEdge

System Properties Comparison Amazon Neptune vs. GigaSpaces vs. Google Cloud Datastore vs. OpenEdge

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonOpenEdge  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformApplication development environment with integrated database management system
Primary database modelGraph DBMS
RDF store
Document store
Object oriented DBMS infoValues are user defined objects
Document storeRelational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score3.51
Rank#86  Overall
#46  Relational DBMS
Websiteaws.amazon.com/­neptunewww.gigaspaces.comcloud.google.com/­datastorewww.progress.com/­openedge
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.gigaspaces.com/­latest/­landing.htmlcloud.google.com/­datastore/­docsdocumentation.progress.com/­output/­ua/­OpenEdge_latest
DeveloperAmazonGigaspaces TechnologiesGoogleProgress Software Corporation
Initial release2017200020081984
Current release15.5, September 2020OpenEdge 12.2, March 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .Net
Server operating systemshostedLinux
macOS
Solaris
Windows
hostedAIX
HP-UX
Linux
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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.nono infoXML can be used for describing objects metadatanoyes
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoSQL-99 for query and DML statementsSQL-like query language (GQL)yes infoclose to SQL 92
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C++
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Progress proprietary ABL (Advanced Business Language)
Server-side scripts infoStored proceduresnoyesusing Google App Engineyes
Triggersnoyes, event driven architectureCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardinghorizontal 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.Multi-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate 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 Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Role-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users and groups

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More resources
Amazon NeptuneGigaSpacesGoogle Cloud DatastoreOpenEdge
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