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DBMS > Ingres vs. NSDb vs. Spark SQL vs. Tigris

System Properties Comparison Ingres vs. NSDb vs. Spark SQL vs. Tigris

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Editorial information provided by DB-Engines
NameIngres  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigris  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 horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelRelational DBMSTime Series DBMSRelational DBMSDocument store
Key-value store
Search engine
Time Series 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
Score0.02
Rank#369  Overall
#51  Document stores
#55  Key-value stores
#24  Search engines
#38  Time Series DBMS
Websitewww.actian.com/­databases/­ingresnsdb.iospark.apache.org/­sqlwww.tigrisdata.com
Technical documentationdocs.actian.com/­ingresnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tigrisdata.com/­docs
DeveloperActian CorporationApache Software FoundationTigris Data, Inc.
Initial release1974 infooriginally developed at University Berkely in early 1970s201720142022
Current release11.2, May 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
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
Linux
macOS
Windows
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 statementsno
APIs and other access methods.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
gRPC
HTTP REST
WebSocket
JDBC
ODBC
CLI Client
gRPC
RESTful HTTP API
Supported programming languagesJava
Scala
Java
Python
R
Scala
Go
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresyesnonono
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoIngres Star to access multiple databases simultaneouslyShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesIngres Replicatornoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono
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, using FoundationDB
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-standardnoAccess rights for users and roles

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More resources
IngresNSDbSpark SQLTigris
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