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DBMS > Apache Impala vs. Apache IoTDB vs. Elasticsearch vs. Faircom EDGE

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Elasticsearch vs. Faircom EDGE

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  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 metricFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments
Primary database modelRelational DBMSTime Series DBMSSearch engineKey-value store
Relational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score128.79
Rank#8  Overall
#1  Search engines
Score0.02
Rank#370  Overall
#55  Key-value stores
#157  Relational DBMS
Websiteimpala.apache.orgiotdb.apache.orgwww.elastic.co/­elasticsearchwww.faircom.com/­products/­faircom-edge
Technical documentationimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationElasticFairCom Corporation
Initial release2013201820101979
Current release4.1.0, June 20221.1.0, April 20238.6, January 2023V3, October 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoElastic Licensecommercial infoRestricted, free version available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaANSI C, C++
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)All OS with a Java VMAndroid
Linux infoARM, x86
Raspbian
Windows
Data schemeyesyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyesyesyes, ANSI Standard SQL Types
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.nononoyes
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSQL-like query languageyes infoANSI SQL queries
APIs and other access methodsJDBC
ODBC
JDBC
Native API
Java API
RESTful HTTP/JSON API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
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#
C++
Java
JavaScript
PHP
Python
VB.Net
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyesyes info.Net, JavaScript, C/C++
Triggersnoyesyes infoby using the 'percolation' featureyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingFile partitioning infoCustomizable business rules for partitioning
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 replicasyesyes infoSynchronous and asynchronous realtime replication based on transaction logs
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, allImmediate Consistency
Tunable Consistency
Foreign keys infoReferential integritynononoyes infowhen using SQL
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoacross SQL and NoSQL
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 integrationyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

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Apache ImpalaApache IoTDBElasticsearchFaircom EDGE infoformerly c-treeEDGE
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