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DBMS > Apache Phoenix vs. BigObject vs. Google Cloud Spanner vs. TimesTen

System Properties Comparison Apache Phoenix vs. BigObject vs. Google Cloud Spanner vs. TimesTen

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBigObject  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAnalytic DBMS for real-time computations and queriesA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelRelational DBMSRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#125  Overall
#59  Relational DBMS
Score0.13
Rank#329  Overall
#147  Relational DBMS
Score2.69
Rank#101  Overall
#51  Relational DBMS
Score1.26
Rank#164  Overall
#75  Relational DBMS
Websitephoenix.apache.orgbigobject.iocloud.google.com/­spannerwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationphoenix.apache.orgdocs.bigobject.iocloud.google.com/­spanner/­docsdocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperApache Software FoundationBigObject, Inc.GoogleOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2014201520171998
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019Release 22.1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemsLinux
Unix
Windows
Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedIBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes infoQuery statements complying to ANSI 2011yes
APIs and other access methodsJDBCfluentd
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Java
JavaScript (Node.js)
Python
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresuser defined functionsLuanoPL/SQL
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneMulti-source replication with 3 replicas for regional instances.Multi-source replication
Source-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 ConsistencynoneImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoStrict serializable isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes
Durability infoSupport for making data persistentyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Apache PhoenixBigObjectGoogle Cloud SpannerTimesTen
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