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DBMS > Apache Impala vs. Apache IoTDB vs. Hazelcast vs. IBM Db2 Event Store

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Hazelcast vs. IBM Db2 Event Store

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonHazelcast  Xexclude from comparisonIBM Db2 Event Store  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 widely adopted in-memory data gridDistributed Event Store optimized for Internet of Things use cases
Primary database modelRelational DBMSTime Series DBMSKey-value storeEvent Store
Time Series DBMS
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12
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
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Websiteimpala.apache.orgiotdb.apache.orghazelcast.comwww.ibm.com/­products/­db2-event-store
Technical documentationimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhazelcast.org/­imdg/­docswww.ibm.com/­docs/­en/­db2-event-store
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationHazelcastIBM
Initial release2013201820082017
Current release4.1.0, June 20221.1.0, April 20235.3.6, November 20232.0
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaC and C++
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)All OS with a Java VMLinux infoLinux, macOS, Windows for the developer addition
Data schemeyesyesschema-freeyes
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.nonoyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSQL-like query languageyes infothrough the embedded Spark runtime
APIs and other access methodsJDBC
ODBC
JDBC
Native API
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyes infoEvent Listeners, Executor Servicesyes
Triggersnoyesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
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 replicasyes infoReplicated MapActive-active shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceIntegration with Hadoop and Sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutable
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesRole-based access controlfine grained access rights according to SQL-standard

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Apache ImpalaApache IoTDBHazelcastIBM Db2 Event Store
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