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DBMS > Apache Druid vs. Oracle Berkeley DB vs. Realm vs. Spark SQL vs. STSdb

System Properties Comparison Apache Druid vs. Oracle Berkeley DB vs. Realm vs. Spark SQL vs. STSdb

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonRealm  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  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 storeA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
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 DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitedruid.apache.orgwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlrealm.iospark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsOracle infooriginally developed by Sleepycat, which was acquired by OracleRealm, acquired by MongoDB in May 2019Apache Software FoundationSTS Soft SC
Initial release20121994201420142011
Current release29.0.1, April 202418.1.40, May 20203.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infocommercial license availableOpen SourceOpen Source infoApache 2.0Open Source infoGPLv2, commercial license available
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)ScalaC#
Server operating systemsLinux
OS X
Unix
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Android
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Windows
Data schemeyes infoschema-less columns are supportedschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes infoprimitive types and user defined types (classes)
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 editionnono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLSQL for queryingyes infoSQL interfaced based on SQLite is availablenoSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
.NET Client 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
.Net
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresnonono inforuns within the applications so server-side scripts are unnecessarynono
Triggersnoyes infoonly for the SQL APIyes infoChange Listenersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednonenoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyesyes infoIn-Memory realmno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoyesnono

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Apache DruidOracle Berkeley DBRealmSpark SQLSTSdb
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