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DBMS > Databend vs. GeoMesa vs. Informix vs. Spark SQL vs. Transbase

System Properties Comparison Databend vs. GeoMesa vs. Informix vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGeoMesa  Xexclude from comparisonInformix  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  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 complexityGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSSpatial 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score17.12
Rank#34  Overall
#21  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.geomesa.orgwww.ibm.com/­products/­informixspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.databend.comwww.geomesa.org/­documentation/­stable/­user/­index.htmlinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
spark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperDatabend LabsCCRi and othersIBM, 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 FoundationTransaction Software GmbH
Initial release20212014198420141987
Current release1.0.59, April 20235.0.0, May 202414.10.FC5, November 20203.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache License 2.0commercial infofree developer edition availableOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustScalaC, C++ and JavaScalaC and C++
Server operating systemshosted
Linux
macOS
AIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes 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.nononono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLyesnoyesSQL-like DML and DDL statementsyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnonoyesnoyes
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnonedepending on storage layerShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnonedepending on storage layerMulti-source replication
Source-replica replication
noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistencydepending on storage layerImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACIDnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.depending on storage layeryesnono
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesyes infodepending on the DBMS used for storageUsers with fine-grained authentication, authorization, and auditing controlsnofine grained access rights according to SQL-standard

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More resources
DatabendGeoMesaInformixSpark SQLTransbase
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