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DBMS > Apache Phoenix vs. BaseX vs. Google Cloud Datastore vs. Spark SQL vs. Transbase

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

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBaseX  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSNative XML DBMSDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score1.84
Rank#135  Overall
#4  Native XML DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitephoenix.apache.orgbasex.orgcloud.google.com/­datastorespark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationphoenix.apache.orgdocs.basex.orgcloud.google.com/­datastore/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software FoundationBaseX GmbHGoogleApache Software FoundationTransaction Software GmbH
Initial release20142007200820141987
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201911.0, June 20243.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSD licensecommercialOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScalaC and C++
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
hostedLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesno infoXQuery supports typesyes, 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.nononono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyesnoSQL-like query language (GQL)SQL-like DML and DDL statementsyes
APIs and other access methodsJDBCJava API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Actionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsyesusing Google App Enginenoyes
Triggersnoyes infovia eventsCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneMulti-source replication using PaxosnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes 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.Immediate Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDmultiple readers, single writerACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyUsers with fine-grained authorization concept on 4 levelsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
Apache PhoenixBaseXGoogle Cloud DatastoreSpark SQLTransbase
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