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DBMS > Apache Druid vs. Badger vs. Spark SQL vs. STSdb

System Properties Comparison Apache Druid vs. Badger vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBadger  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 dataAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Spark 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 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
Score0.22
Rank#320  Overall
#47  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitedruid.apache.orggithub.com/­dgraph-io/­badgerspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationdruid.apache.org/­docs/­latest/­designgodoc.org/­github.com/­dgraph-io/­badgerspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsDGraph LabsApache Software FoundationSTS Soft SC
Initial release2012201720142011
Current release29.0.1, April 20243.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache 2.0Open Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoScalaC#
Server operating systemsLinux
OS X
Unix
BSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Windows
Data schemeyes infoschema-less columns are supportedschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes 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.nonono
Secondary indexesyesnonono
SQL infoSupport of SQLSQL for queryingnoSQL-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
GoJava
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistencynone
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnonono

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More resources
Apache DruidBadgerSpark SQLSTSdb
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