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DBMS > Apache Pinot vs. Google Cloud Bigtable vs. Kdb vs. Oracle Berkeley DB

System Properties Comparison Apache Pinot vs. Google Cloud Bigtable vs. Kdb vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKdb  Xexclude from comparisonOracle Berkeley DB  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.High performance Time Series DBMSWidely used in-process key-value store
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMS
Vector DBMS
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Websitepinot.apache.orgcloud.google.com/­bigtablekx.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdocs.pinot.apache.orgcloud.google.com/­bigtable/­docscode.kx.comdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperApache Software Foundation and contributorsGoogleKx Systems, a division of First Derivatives plcOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release201520152000 infokdb was released 2000, kdb+ in 20031994
Current release1.0.0, September 20233.6, May 201818.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree 32-bit versionOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaqC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsAll OS with a Java JDK11 or higherhostedLinux
OS X
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesno
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.noyesyes infoonly with the Berkeley DB XML edition
Secondary indexesnoyes infotable attribute 'grouped'yes
SQL infoSupport of SQLSQL-like query languagenoSQL-like query language (q)yes infoSQL interfaced based on SQLite is available
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesGo
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresnouser defined functionsno
Triggersnoyes infowith viewsyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardinghorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno infosimilar paradigm used for internal processingno
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
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accountsno
More information provided by the system vendor
Apache PinotGoogle Cloud BigtableKdbOracle Berkeley DB
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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Apache PinotGoogle Cloud BigtableKdbOracle Berkeley DB
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