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DBMS > Apache Impala vs. Oracle Berkeley DB vs. Spark SQL vs. TerarkDB vs. Transbase

System Properties Comparison Apache Impala vs. Oracle Berkeley DB vs. Spark SQL vs. TerarkDB vs. Transbase

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDBA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score2.52
Rank#114  Overall
#20  Key-value stores
#3  Native XML DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#377  Overall
#58  Key-value stores
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websiteimpala.apache.orgwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­bytedance/­terarkdbwww.transaction.de/­en/­products/­transbase.html
Technical documentationimpala.apache.org/­impala-docs.htmldocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKcwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationByteDance, originally TerarkTransaction Software GmbH
Initial release20131994201420161987
Current release4.1.0, June 202218.1.40, May 20203.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infocommercial license availableOpen Source infoApache 2.0commercial inforestricted open source version availablecommercial 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 languageC++C, Java, C++ (depending on the Berkeley DB edition)ScalaC++C and C++
Server operating systemsLinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesnoyes
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 indexesyesyesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
C++ API
Java API
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesAll languages supporting JDBC/ODBC.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
C++
Java
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenononoyes
Triggersnoyes infoonly for the SQL APInonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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 datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnononofine grained access rights according to SQL-standard

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More resources
Apache ImpalaOracle Berkeley DBSpark SQLTerarkDBTransbase
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