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DBMS > Apache Druid vs. Oracle Berkeley DB vs. PouchDB vs. Spark SQL vs. Transbase

System Properties Comparison Apache Druid vs. Oracle Berkeley DB vs. PouchDB vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonPouchDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataWidely used in-process key-value storeJavaScript DBMS with an API inspired by CouchDBSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMS
Time Series DBMS
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Document storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitedruid.apache.orgwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlpouchdb.comspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlpouchdb.com/­guidesspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software Foundation and contributorsOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationApache Software FoundationTransaction Software GmbH
Initial release20121994201220141987
Current release29.0.1, April 202418.1.40, May 20207.1.1, June 20193.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infocommercial license availableOpen SourceOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, Java, C++ (depending on the Berkeley DB edition)JavaScriptScalaC and C++
Server operating systemsLinux
OS X
Unix
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnonoyesyes
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 infoonly with the Berkeley DB XML editionnonono
Secondary indexesyesyesyes infovia viewsnoyes
SQL infoSupport of SQLSQL for queryingyes infoSQL interfaced based on SQLite is availablenoSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
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
JavaScriptJava
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnonoView functions in JavaScriptnoyes
Triggersnoyes infoonly for the SQL APIyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneSharding infowith a proxy-based framework, named couchdb-loungeyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesnono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnononofine grained access rights according to SQL-standard

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More resources
Apache DruidOracle Berkeley DBPouchDBSpark SQLTransbase
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