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DBMS > GeoMesa vs. Greenplum vs. InfinityDB vs. MarkLogic vs. Spark SQL

System Properties Comparison GeoMesa vs. Greenplum vs. InfinityDB vs. MarkLogic vs. Spark SQL

Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonGreenplum  Xexclude from comparisonInfinityDB  Xexclude from comparisonMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A Java embedded Key-Value Store which extends the Java Map interfaceOperational and transactional Enterprise NoSQL databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelSpatial DBMSRelational DBMSKey-value storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score0.08
Rank#365  Overall
#55  Key-value stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.geomesa.orggreenplum.orgboilerbay.comwww.progress.com/­marklogicspark.apache.org/­sql
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.greenplum.orgboilerbay.com/­infinitydb/­manualwww.progress.com/­marklogic/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCCRi and othersPivotal Software Inc.Boiler Bay Inc.MarkLogic Corp.Apache Software Foundation
Initial release20142005200220012014
Current release5.0.0, May 20247.0.0, September 20234.011.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache 2.0commercialcommercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJavaC++Scala
Server operating systemsLinuxAll OS with a Java VMLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyesyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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 infosince Version 4.2noyesno
Secondary indexesyesyesno infomanual creation possible, using inversions based on multi-value capabilityyesno
SQL infoSupport of SQLnoyesnoyes infoSQL92SQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
JDBC
ODBC
Supported programming languagesC
Java
Perl
Python
R
JavaC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnoyes infovia XQuery or JavaScriptno
Triggersnoyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerShardingnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerSource-replica replicationnoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integritynoyesno infomanual creation possible, using inversions based on multi-value capabilitynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsACID infocan act as a resource manager in an XA/JTA transactionno
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 layernonoyes, with Range Indexesno
User concepts infoAccess controlyes infodepending on the DBMS used for storagefine grained access rights according to SQL-standardnoRole-based access control at the document and subdocument levelsno

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More resources
GeoMesaGreenplumInfinityDBMarkLogicSpark SQL
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