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DBMS > Brytlyt vs. JaguarDB vs. Oracle Berkeley DB vs. PouchDB vs. Spark SQL

System Properties Comparison Brytlyt vs. JaguarDB vs. Oracle Berkeley DB vs. PouchDB vs. Spark SQL

Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonJaguarDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonPouchDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLPerformant, highly scalable DBMS for AI and IoT applicationsWidely 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 processing
Primary database modelRelational DBMSKey-value store
Vector DBMS
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Document storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector 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
Websitebrytlyt.iowww.jaguardb.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlpouchdb.comspark.apache.org/­sql
Technical documentationdocs.brytlyt.iowww.jaguardb.com/­support.htmldocs.oracle.com/­cd/­E17076_05/­html/­index.htmlpouchdb.com/­guidesspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBrytlytDataJaguar, Inc.Oracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationApache Software Foundation
Initial release20162015199420122014
Current release5.0, August 20233.3 July 202318.1.40, May 20207.1.1, June 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL V3.0Open Source infocommercial license availableOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and CUDAC++ infothe server part. Clients available in other languagesC, Java, C++ (depending on the Berkeley DB edition)JavaScriptScala
Server operating systemsLinux
OS X
Windows
LinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnonoyes
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.yes infospecific XML-type available, but no XML query functionality.noyes infoonly with the Berkeley DB XML editionnono
Secondary indexesyesyesyesyes infovia viewsno
SQL infoSupport of SQLyesA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersyes infoSQL interfaced based on SQLite is availablenoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
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
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLnonoView functions in JavaScriptno
Triggersyesnoyes infoonly for the SQL APIyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infowith a proxy-based framework, named couchdb-loungeyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationSource-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardrights management via user accountsnonono

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More resources
BrytlytJaguarDBOracle Berkeley DBPouchDBSpark SQL
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