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DBMS > Apache Impala vs. Citus vs. etcd vs. Hazelcast

System Properties Comparison Apache Impala vs. Citus vs. etcd vs. Hazelcast

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCitus  Xexclude from comparisonetcd  Xexclude from comparisonHazelcast  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA distributed reliable key-value storeA widely adopted in-memory data grid
Primary database modelRelational DBMSRelational DBMSKey-value storeKey-value store
Secondary database modelsDocument storeDocument storeDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score2.13
Rank#117  Overall
#56  Relational DBMS
Score7.05
Rank#53  Overall
#5  Key-value stores
Score5.72
Rank#59  Overall
#6  Key-value stores
Websiteimpala.apache.orgwww.citusdata.cometcd.io
github.com/­etcd-io/­etcd
hazelcast.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.citusdata.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
hazelcast.org/­imdg/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHazelcast
Initial release201320102008
Current release4.1.0, June 20228.1, December 20183.4, August 20195.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL, commercial license also availableOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CGoJava
Server operating systemsLinuxLinuxFreeBSD
Linux
Windows infoexperimental
All OS with a Java VM
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnoyes
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 infospecific XML type available, but no XML query functionalitynoyes infothe object must implement a serialization strategy
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard, with numerous extensionsnoSQL-like query language
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC
JSON over HTTP
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes infoEvent Listeners, Executor Services
Triggersnoyesyes, watching key changesyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication infoother methods possible by using 3rd party extensionsUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoone or two-phase-commit; repeatable reads; read commited
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.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardnoRole-based access control

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More resources
Apache ImpalaCitusetcdHazelcast
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