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DBMS > ArcadeDB vs. Google Cloud Datastore vs. Riak KV vs. SQream DB

System Properties Comparison ArcadeDB vs. Google Cloud Datastore vs. Riak KV vs. SQream DB

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Editorial information provided by DB-Engines
NameArcadeDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRiak KV  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed, fault tolerant key-value storea GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Document storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.10
Rank#358  Overall
#48  Document stores
#38  Graph DBMS
#52  Key-value stores
#35  Time Series DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Score0.74
Rank#224  Overall
#103  Relational DBMS
Websitearcadedb.comcloud.google.com/­datastoresqream.com
Technical documentationdocs.arcadedb.comcloud.google.com/­datastore/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latestdocs.sqream.com
DeveloperArcade DataGoogleOpenSource, formerly Basho TechnologiesSQream Technologies
Initial release2021200820092017
Current releaseSeptember 20213.2.0, December 20222022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache version 2, commercial enterprise editioncommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaErlangC++, CUDA, Haskell, Java, Scala
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Linux
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details herenoyes, ANSI Standard SQL Types
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 indexesyesyesrestrictedno
SQL infoSupport of SQLSQL-like query language, no joinsSQL-like query language (GQL)noyes
APIs and other access methodsJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Native Erlang Interface
.Net
JDBC
ODBC
Supported programming languagesJava.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
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
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresusing Google App EngineErlanguser defined functions in Python
TriggersCallbacks using the Google Apps Engineyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"horizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using Paxosselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesno
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.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes inforelationship in graphsyes infovia ReferenceProperties or Ancestor pathsno infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes, using Riak Security

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More resources
ArcadeDBGoogle Cloud DatastoreRiak KVSQream DB
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