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DBMS > Google Cloud Bigtable vs. Greenplum vs. PouchDB vs. Spark SQL vs. TimesTen

System Properties Comparison Google Cloud Bigtable vs. Greenplum vs. PouchDB vs. Spark SQL vs. TimesTen

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGreenplum  Xexclude from comparisonPouchDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.JavaScript DBMS with an API inspired by CouchDBSpark SQL is a component on top of 'Spark Core' for structured data processingIn-Memory RDBMS compatible to Oracle
Primary database modelKey-value store
Wide column store
Relational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitecloud.google.com/­bigtablegreenplum.orgpouchdb.comspark.apache.org/­sqlwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationcloud.google.com/­bigtable/­docsdocs.greenplum.orgpouchdb.com/­guidesspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.oracle.com/­database/­timesten-18.1
DeveloperGooglePivotal Software Inc.Apache Software FoundationApache Software FoundationOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20152005201220141998
Current release7.0.0, September 20237.1.1, June 20193.5.0 ( 2.13), September 202311 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open SourceOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptScala
Server operating systemshostedLinuxserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or datenoyesnoyesyes
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.noyes infosince Version 4.2nonono
Secondary indexesnoyesyes infovia viewsnoyes
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statementsyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
Java
Perl
Python
R
JavaScriptJava
Python
R
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnoyesView functions in JavaScriptnoPL/SQL
Triggersnoyesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infowith a proxy-based framework, named couchdb-loungeyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes 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.nonoyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardnonofine grained access rights according to SQL-standard

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More resources
Google Cloud BigtableGreenplumPouchDBSpark SQLTimesTen
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