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DBMS > Ingres vs. NSDb vs. Spark SQL vs. TDSQL for MySQL

System Properties Comparison Ingres vs. NSDb vs. Spark SQL vs. TDSQL for MySQL

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Editorial information provided by DB-Engines
NameIngres  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionWell established RDBMSScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesSpark SQL is a component on top of 'Spark Core' for structured data processingA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.85
Rank#205  Overall
#95  Relational DBMS
Websitewww.actian.com/­databases/­ingresnsdb.iospark.apache.org/­sqlwww.tencentcloud.com/­products/­dcdb
Technical documentationdocs.actian.com/­ingresnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tencentcloud.com/­document/­product/­1042
DeveloperActian CorporationApache Software FoundationTencent
Initial release1974 infooriginally developed at University Berkely in early 1970s201720142013
Current release11.2, May 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava, ScalaScala
Server operating systemsAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
macOS
Linux
OS X
Windows
hosted
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes: int, bigint, decimal, stringyesyes
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.no infobut tools for importing/exporting data from/to XML-files availablenonono
Secondary indexesyesall fields are automatically indexednoyes
SQL infoSupport of SQLyesSQL-like query languageSQL-like DML and DDL statementsyes
APIs and other access methods.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
gRPC
HTTP REST
WebSocket
JDBC
ODBC
JDBC
ODBC
Supported programming languagesJava
Scala
Java
Python
R
Scala
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesnonoyes
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoIngres Star to access multiple databases simultaneouslyShardingyes, utilizing Spark CoreAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesIngres ReplicatornoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual 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 datayes infoMVCCyesyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardnoUsers with fine-grained authorization concept

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More resources
IngresNSDbSpark SQLTDSQL for MySQL
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