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DBMS > Badger vs. LeanXcale vs. Spark SQL vs. SQream DB vs. STSdb

System Properties Comparison Badger vs. LeanXcale vs. Spark SQL vs. SQream DB vs. STSdb

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonLeanXcale  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesSpark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloadsKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelKey-value storeKey-value store
Relational DBMS
Relational DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.74
Rank#224  Overall
#103  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitegithub.com/­dgraph-io/­badgerwww.leanxcale.comspark.apache.org/­sqlsqream.comgithub.com/­STSSoft/­STSdb4
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.com
DeveloperDGraph LabsLeanXcaleApache Software FoundationSQream TechnologiesSTS Soft SC
Initial release20172015201420172011
Current release3.5.0 ( 2.13), September 20232022.1.6, December 20224.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0commercialOpen 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 languageGoScalaC++, CUDA, Haskell, Java, ScalaC#
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
LinuxWindows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or datenoyesyes, ANSI Standard SQL Typesyes 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.nono
Secondary indexesnononono
SQL infoSupport of SQLnoyes infothrough Apache DerbySQL-like DML and DDL statementsyesno
APIs and other access methodsJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
ODBC
.Net
JDBC
ODBC
.NET Client API
Supported programming languagesGoC
Java
Scala
Java
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
C#
Java
Server-side scripts infoStored proceduresnonouser defined functions in Pythonno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Corehorizontal and vertical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyesno
User concepts infoAccess controlnonono

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More resources
BadgerLeanXcaleSpark SQLSQream DBSTSdb
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