DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. GeoMesa vs. MonetDB vs. ObjectBox

System Properties Comparison Apache Impala vs. GeoMesa vs. MonetDB vs. ObjectBox

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGeoMesa  Xexclude from comparisonMonetDB  Xexclude from comparisonObjectBox  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.A relational database management system that stores data in columnsExtremely fast embedded database for small devices, IoT and Mobile
Primary database modelRelational DBMSSpatial DBMSRelational DBMSObject oriented DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Websiteimpala.apache.orgwww.geomesa.orgwww.monetdb.orgobjectbox.io
Technical documentationimpala.apache.org/­impala-docs.htmlwww.geomesa.org/­documentation/­stable/­user/­index.htmlwww.monetdb.org/­Documentationdocs.objectbox.io
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCCRi and othersMonetDB BVObjectBox Limited
Initial release2013201420042017
Current release4.1.0, June 20225.0.0, May 2024Dec2023 (11.49), December 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache License 2.0Open Source infoMozilla Public License 2.0Open Source infoApache License 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 languageC++ScalaCC and C++
Server operating systemsLinuxFreeBSD
Linux
OS X
Solaris
Windows
Android
iOS
Linux
macOS
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infoSQL 2003 with some extensionsno
APIs and other access methodsJDBC
ODBC
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Proprietary native API
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes, in SQL, C, Rno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingdepending on storage layerSharding via remote tablesnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factordepending on storage layernone infoSource-replica replication available in experimental statusonline/offline synchronization between client and server
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistencydepending on storage layerImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
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.nodepending on storage layerno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes infodepending on the DBMS used for storagefine grained access rights according to SQL-standardyes
More information provided by the system vendor
Apache ImpalaGeoMesaMonetDBObjectBox
News

The on-device Vector Database for Android and Java
29 May 2024

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

Evolution of search: traditional vs vector search
23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaGeoMesaMonetDBObjectBox
DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

In 2024 the MonetDB Foundation was established for the preservation, maintenance and further development of the ...
31 January 2024, Centrum Wiskunde & Informatica (CWI)

MonetDB Secures Investment From (and Partners With) ServiceNow
9 December 2021, Datanami

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R - Part I - DataScienceCentral.com
6 April 2018, Data Science Central

How MonetDB Exploits Modern CPU Performance | by Dwi Prasetyo Adi Nugroho
14 January 2020, Towards Data Science

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R - Part II - DataScienceCentral.com
13 June 2018, Data Science Central

provided by Google News

The Megashift Towards Decentralized Edge Computing
27 August 2021, hackernoon.com

provided by Google News



Share this page

Featured Products

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here