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

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

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonIngres  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityWell 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 processing
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
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
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.actian.com/­databases/­ingresnsdb.iospark.apache.org/­sql
Technical documentationdocs.databend.comdocs.actian.com/­ingresnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabend LabsActian CorporationApache Software Foundation
Initial release20211974 infooriginally developed at University Berkely in early 1970s20172014
Current release1.0.59, April 202311.2, May 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageRustCJava, ScalaScala
Server operating systemshosted
Linux
macOS
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
macOS
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringyes
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 infobut tools for importing/exporting data from/to XML-files availablenono
Secondary indexesnoyesall fields are automatically indexedno
SQL infoSupport of SQLyesyesSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
gRPC
HTTP REST
WebSocket
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnono
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning infoIngres Star to access multiple databases simultaneouslyShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneIngres Replicatornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesfine grained access rights according to SQL-standardno

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More resources
DatabendIngresNSDbSpark SQL
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