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DBMS > Databend vs. Informix vs. Postgres-XL vs. Spark SQL

System Properties Comparison Databend vs. Informix vs. Postgres-XL vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonInformix  Xexclude from comparisonPostgres-XL  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 complexityA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score17.87
Rank#35  Overall
#22  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.ibm.com/­products/­informixwww.postgres-xl.orgspark.apache.org/­sql
Technical documentationdocs.databend.cominformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
www.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabend LabsIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Apache Software Foundation
Initial release202119842014 infosince 2012, originally named StormDB2014
Current release1.0.59, April 202314.10.FC5, November 202010 R1, October 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree developer edition availableOpen Source infoMozilla public licenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustC, C++ and JavaCScala
Server operating systemshosted
Linux
macOS
AIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
macOS
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infoSince Version 12.10 support for JSON/BSON datatypesyesyes
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.noyes infoXML type, but no XML query functionalityno
Secondary indexesnoyesyesno
SQL infoSupport of SQLyesyesyes infodistributed, parallel query executionSQL-like DML and DDL statements
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesuser defined functionsno
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACID infoMVCCno
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.yesnono
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesUsers with fine-grained authentication, authorization, and auditing controlsfine grained access rights according to SQL-standardno

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More resources
DatabendInformixPostgres-XLSpark SQL
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