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DBMS > GeoMesa vs. Greenplum vs. GridDB vs. QuestDB

System Properties Comparison GeoMesa vs. Greenplum vs. GridDB vs. QuestDB

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonGreenplum  Xexclude from comparisonGridDB  Xexclude from comparisonQuestDB  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.Scalable in-memory time series database optimized for IoT and Big DataA high performance open source SQL database for time series data
Primary database modelSpatial DBMSRelational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Key-value store
Relational DBMS
Relational 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
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Websitewww.geomesa.orggreenplum.orggriddb.netquestdb.io
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.greenplum.orgdocs.griddb.netquestdb.io/­docs
DeveloperCCRi and othersPivotal Software Inc.Toshiba CorporationQuestDB Technology Inc
Initial release2014200520132014
Current release5.0.0, May 20247.0.0, September 20235.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen 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 languageScalaC++Java (Zero-GC), C++, Rust
Server operating systemsLinuxLinuxLinux
macOS
Windows
Data schemeyesyesyesyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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 4.2nono
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoyesSQL92, SQL-like TQL (Toshiba Query Language)SQL with time-series extensions
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesC
Java
Perl
Python
R
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresnoyesnono
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerShardingShardinghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerSource-replica replicationSource-replica replicationSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container levelACID for single-table writes
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.depending on storage layernoyesyes infothrough memory mapped files
User concepts infoAccess controlyes infodepending on the DBMS used for storagefine grained access rights according to SQL-standardAccess rights for users can be defined per database
More information provided by the system vendor
GeoMesaGreenplumGridDBQuestDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Financial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
GeoMesaGreenplumGridDBQuestDB
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