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DBMS > EJDB vs. Oracle Berkeley DB vs. Spark SQL vs. Tigris vs. Transbase

System Properties Comparison EJDB vs. Oracle Berkeley DB vs. Spark SQL vs. Tigris vs. Transbase

Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigris  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Widely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructureA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelDocument storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSDocument store
Key-value store
Search engine
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#296  Overall
#44  Document stores
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.09
Rank#363  Overall
#49  Document stores
#54  Key-value stores
#22  Search engines
#38  Time Series DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlwww.tigrisdata.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tigrisdata.com/­docswww.transaction.de/­en/­products/­transbase/­features.html
DeveloperSoftmotionsOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationTigris Data, Inc.Transaction Software GmbH
Initial release20121994201420221987
Current release18.1.40, May 20203.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoGPLv2Open Source infocommercial license availableOpen Source infoApache 2.0Open Source infoApache Version 2.0commercial infofree development license
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 languageCC, Java, C++ (depending on the Berkeley DB edition)ScalaC and C++
Server operating systemsserver-lessAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Linux
macOS
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idnoyesyesyes
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 infoonly with the Berkeley DB XML editionnonono
Secondary indexesnoyesnoyesyes
SQL infoSupport of SQLnoyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsnoyes
APIs and other access methodsin-process shared libraryJDBC
ODBC
CLI Client
gRPC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.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
Java
Python
R
Scala
Go
Java
JavaScript (Node.js)
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnonononoyes
Triggersnoyes infoonly for the SQL APInonoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationnoneyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possiblenonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDyes
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using FoundationDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlnononoAccess rights for users and rolesfine grained access rights according to SQL-standard

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More resources
EJDBOracle Berkeley DBSpark SQLTigrisTransbase
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