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DBMS > Apache Pinot vs. Google Cloud Bigtable vs. HBase vs. MonetDB

System Properties Comparison Apache Pinot vs. Google Cloud Bigtable vs. HBase vs. MonetDB

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHBase  Xexclude from comparisonMonetDB  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Wide-column store based on Apache Hadoop and on concepts of BigTableA relational database management system that stores data in columns
Primary database modelRelational DBMSKey-value store
Wide column store
Wide column storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score1.72
Rank#141  Overall
#64  Relational DBMS
Websitepinot.apache.orgcloud.google.com/­bigtablehbase.apache.orgwww.monetdb.org
Technical documentationdocs.pinot.apache.orgcloud.google.com/­bigtable/­docshbase.apache.org/­book.htmlwww.monetdb.org/­Documentation
DeveloperApache Software Foundation and contributorsGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetMonetDB BV
Initial release2015201520082004
Current release1.0.0, September 20232.3.4, January 2021Dec2023 (11.49), December 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache version 2Open Source infoMozilla Public License 2.0
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 languageJavaJavaC
Server operating systemsAll OS with a Java JDK11 or higherhostedLinux
Unix
Windows infousing Cygwin
FreeBSD
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesnooptions to bring your own types, AVROyes
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.nono
Secondary indexesnonoyes
SQL infoSupport of SQLSQL-like query languagenonoyes infoSQL 2003 with some extensions
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
Thrift
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languagesGo
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javayes, in SQL, C, R
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingSharding via remote tables
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
none infoSource-replica replication available in experimental status
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsSingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standard

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Apache PinotGoogle Cloud BigtableHBaseMonetDB
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