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DBMS > Apache Phoenix vs. Google Cloud Datastore vs. Spark SQL vs. VoltDB

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

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSpark SQL  Xexclude from comparisonVoltDB  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 PlatformSpark SQL is a component on top of 'Spark Core' for structured data processingDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score1.46
Rank#159  Overall
#74  Relational DBMS
Websitephoenix.apache.orgcloud.google.com/­datastorespark.apache.org/­sqlwww.voltdb.com
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.voltdb.com
DeveloperApache Software FoundationGoogleApache Software FoundationVoltDB Inc.
Initial release2014200820142010
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.5.0 ( 2.13), September 202311.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
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 languageJavaScalaJava, C++
Server operating systemsLinux
Unix
Windows
hostedLinux
OS X
Windows
Linux
OS X infofor development
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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 indexesyesyesnoyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like DML and DDL statementsyes infoonly a subset of SQL 99
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsusing Google App EnginenoJava
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using PaxosnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes infousing Google Cloud Dataflowno
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.
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyes infoSnapshots and command logging
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)noUsers and roles with access to stored procedures

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More resources
Apache PhoenixGoogle Cloud DatastoreSpark SQLVoltDB
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