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DBMS > Amazon Neptune vs. EJDB vs. Google Cloud Datastore vs. TimesTen

System Properties Comparison Amazon Neptune vs. EJDB vs. Google Cloud Datastore vs. TimesTen

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonEJDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformIn-Memory RDBMS compatible to Oracle
Primary database modelGraph DBMS
RDF store
Document storeDocument storeRelational 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
Score0.31
Rank#296  Overall
#44  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websiteaws.amazon.com/­neptunegithub.com/­Softmotions/­ejdbcloud.google.com/­datastorewww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationaws.amazon.com/­neptune/­developer-resourcesgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­datastore/­docsdocs.oracle.com/­database/­timesten-18.1
DeveloperAmazonSoftmotionsGoogleOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2017201220081998
Current release11 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourcecommercialOpen Source infoGPLv2commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC
Server operating systemshostedserver-lesshostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyes, 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.nonono
Secondary indexesnonoyesyes
SQL infoSupport of SQLnonoSQL-like query language (GQL)yes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
in-process shared librarygRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnonousing Google App EnginePL/SQL
TriggersnonoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingnone
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.noneMulti-source replication using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
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 Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoRelationships in graphsno infotypically not needed, however similar functionality with collection joins possibleyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Amazon NeptuneEJDBGoogle Cloud DatastoreTimesTen
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