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DBMS > Linter vs. Spark SQL vs. STSdb vs. YDB

System Properties Comparison Linter vs. Spark SQL vs. STSdb vs. YDB

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Editorial information provided by DB-Engines
NameLinter  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonYDB  Xexclude from comparison
DescriptionRDBMS for high security requirementsSpark 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 methodA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelRelational DBMSRelational DBMSKey-value storeDocument store
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websitelinter.ruspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4github.com/­ydb-platform/­ydb
ydb.tech
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlydb.tech/­en/­docs
Developerrelex.ruApache Software FoundationSTS Soft SCYandex
Initial release1990201420112019
Current release3.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license availableOpen Source infoApache 2.0; 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 languageC and C++ScalaC#
Server operating systemsAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
OS X
Windows
WindowsLinux
Data schemeyesyesyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyesyes infoprimitive types and user defined types (classes)yes
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 indexesyesnonoyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoSQL-like query language (YQL)
APIs and other access methodsADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
JDBC
ODBC
.NET Client APIRESTful HTTP API (DynamoDB compatible)
Supported programming languagesC
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Java
Python
R
Scala
C#
Java
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresyes infoproprietary syntax with the possibility to convert from PL/SQLnonono
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark CorenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenoneActive-passive shard 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 integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
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.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardnonoAccess rights defined for Yandex Cloud users

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More resources
LinterSpark SQLSTSdbYDB
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