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DBMS > Apache Phoenix vs. Google Cloud Datastore vs. Riak KV vs. Spark SQL

System Properties Comparison Apache Phoenix vs. Google Cloud Datastore vs. Riak KV vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRiak KV  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed, fault tolerant key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument 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
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgcloud.google.com/­datastorespark.apache.org/­sql
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationGoogleOpenSource, formerly Basho TechnologiesApache Software Foundation
Initial release2014200820092014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.2.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaErlangScala
Server operating systemsLinux
Unix
Windows
hostedLinux
OS X
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details herenoyes
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.nononono
Secondary indexesyesyesrestrictedno
SQL infoSupport of SQLyesSQL-like query language (GQL)noSQL-like DML and DDL statements
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.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
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsusing Google App EngineErlangno
TriggersnoCallbacks using the Google Apps Engineyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infono "single point of failure"yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual 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 Consistency
Foreign keys infoReferential integritynoyes 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 Transactionsnono
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.yesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes, using Riak Securityno

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More resources
Apache PhoenixGoogle Cloud DatastoreRiak KVSpark SQL
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