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DBMS > Apache Impala vs. Apache IoTDB vs. Elasticsearch vs. MonetDB

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Elasticsearch vs. MonetDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonMonetDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricA relational database management system that stores data in columns
Primary database modelRelational DBMSTime Series DBMSSearch engineRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score1.72
Rank#145  Overall
#67  Relational DBMS
Websiteimpala.apache.orgiotdb.apache.orgwww.elastic.co/­elasticsearchwww.monetdb.org
Technical documentationimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlwww.monetdb.org/­Documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationElasticMonetDB BV
Initial release2013201820102004
Current release4.1.0, June 20221.1.0, April 20238.6, January 2023Dec2023 (11.49), December 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoElastic LicenseOpen Source infoMozilla Public License 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaC
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)All OS with a Java VMFreeBSD
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyes
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 indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSQL-like query languageyes infoSQL 2003 with some extensions
APIs and other access methodsJDBC
ODBC
JDBC
Native API
Java API
RESTful HTTP/JSON API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyesyes, in SQL, C, R
Triggersnoyesyes infoby using the 'percolation' featureyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding via remote tables
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesnone infoSource-replica replication available in experimental status
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceIntegration with Hadoop and SparkES-Hadoop Connectorno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Strong Consistency with Raft
Eventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
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.noyesMemcached and Redis integration
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyesfine grained access rights according to SQL-standard

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More resources
Apache ImpalaApache IoTDBElasticsearchMonetDB
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