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DBMS > Apache Impala vs. Apache IoTDB vs. Drizzle vs. EDB Postgres vs. Sphinx

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Drizzle vs. EDB Postgres vs. Sphinx

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonDrizzle  Xexclude from comparisonEDB Postgres  Xexclude from comparisonSphinx  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
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 FlinkMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMSSearch engine
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score2.18
Rank#122  Overall
#59  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Websiteimpala.apache.orgiotdb.apache.orgwww.enterprisedb.comsphinxsearch.com
Technical documentationimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.enterprisedb.com/­docssphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationDrizzle project, originally started by Brian AkerEnterpriseDBSphinx Technologies Inc.
Initial release20132018200820052001
Current release4.1.0, June 20221.1.0, April 20237.2.4, September 201214, December 20213.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoGNU GPLcommercial infoBSD for PostgreSQL-componentsOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++CC++
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)FreeBSD
Linux
OS X
Linux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nonoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageyes infowith proprietary extensionsyes infostandard with numerous extensionsSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
JDBC
Native API
JDBCADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
C
C++
Java
PHP
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersnoyesno infohooks for callbacks inside the server can be used.yesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioning infoby hash, list or rangeSharding infoPartitioning is done manually, search queries against distributed index is supported
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 replicasMulti-source replication
Source-replica replication
Multi-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardno

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Apache ImpalaApache IoTDBDrizzleEDB PostgresSphinx
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