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DBMS > Apache Druid vs. GeoMesa vs. Ignite vs. Spark SQL vs. Transbase

System Properties Comparison Apache Druid vs. GeoMesa vs. Ignite vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGeoMesa  Xexclude from comparisonIgnite  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Spark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMS
Time Series DBMS
Spatial DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitedruid.apache.orgwww.geomesa.orgignite.apache.orgspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdruid.apache.org/­docs/­latest/­designwww.geomesa.org/­documentation/­stable/­user/­index.htmlapacheignite.readme.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software Foundation and contributorsCCRi and othersApache Software FoundationApache Software FoundationTransaction Software GmbH
Initial release20122014201520141987
Current release29.0.1, April 20245.0.0, May 2024Apache Ignite 2.63.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache License 2.0Open Source infoApache 2.0Open 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 languageJavaScalaC++, Java, .NetScalaC and C++
Server operating systemsLinux
OS X
Unix
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonoyesnono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL for queryingnoANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnonoyes (compute grid and cache interceptors can be used instead)noyes
Triggersnonoyes (cache interceptors and events)noyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-baseddepending on storage layerShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesdepending on storage layeryes (replicated cache)noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistencydepending on storage layerImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnoyes
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.nodepending on storage layeryesnono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyes infodepending on the DBMS used for storageSecurity Hooks for custom implementationsnofine grained access rights according to SQL-standard

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More resources
Apache DruidGeoMesaIgniteSpark SQLTransbase
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