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DBMS > Google Cloud Datastore vs. Graph Engine vs. GridGain vs. Riak TS

System Properties Comparison Google Cloud Datastore vs. Graph Engine vs. GridGain vs. Riak TS

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonGridGain  Xexclude from comparisonRiak TS  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineGridGain is an in-memory computing platform, built on Apache IgniteRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelDocument storeGraph DBMS
Key-value store
Key-value store
Relational DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.28
Rank#307  Overall
#27  Time Series DBMS
Websitecloud.google.com/­datastorewww.graphengine.iowww.gridgain.com
Technical documentationcloud.google.com/­datastore/­docswww.graphengine.io/­docs/­manualwww.gridgain.com/­docs/­index.htmlwww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperGoogleMicrosoftGridGain Systems, Inc.Open Source, formerly Basho Technologies
Initial release2008201020072015
Current releaseGridGain 8.5.13.0.0, September 2022
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicensecommercialOpen Source
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation language.NET and CJava, C++, .NetErlang
Server operating systemshosted.NETLinux
OS X
Solaris
Windows
Linux
OS X
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesno
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.nonoyesno
Secondary indexesyesyesrestricted
SQL infoSupport of SQLSQL-like query language (GQL)noANSI-99 for query and DML statements, subset of DDLyes, limited
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
Native Erlang Interface
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
F#
Visual Basic
C#
C++
Java
PHP
Python
Ruby
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresusing Google App Engineyesyes (compute grid and cache interceptors can be used instead)Erlang
TriggersCallbacks using the Google Apps Enginenoyes (cache interceptors and events)yes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes (replicated cache)selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)yes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesoptional: 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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsno

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More resources
Google Cloud DatastoreGraph Engine infoformer name: TrinityGridGainRiak TS
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