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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFatDB  Xexclude from comparisonHazelcast  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAnalytic DBMS for HadoopA .NET NoSQL DBMS that can integrate with and extend SQL Server.A widely adopted in-memory data gridDistributed Event Store optimized for Internet of Things use cases
Primary database modelRelational DBMSDocument store
Key-value store
Key-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
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Websiteimpala.apache.orghazelcast.comwww.ibm.com/­products/­db2-event-store
Technical documentationimpala.apache.org/­impala-docs.htmlhazelcast.org/­imdg/­docswww.ibm.com/­docs/­en/­db2-event-store
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaFatCloudHazelcastIBM
Initial release2013201220082017
Current release4.1.0, June 20225.3.6, November 20232.0
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen 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++C#JavaC and C++
Server operating systemsLinuxWindowsAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer addition
Data schemeyesschema-freeschema-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.noyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsno infoVia inetgration in SQL ServerSQL-like query languageyes infothrough the embedded Spark runtime
APIs and other access methodsJDBC
ODBC
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC#.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-reduceyes infovia applicationsyes infoEvent Listeners, Executor Servicesyes
Triggersnoyes infovia applicationsyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factoryes infoReplicated MapActive-active shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno infoCan implement custom security layer via applicationsRole-based access controlfine grained access rights according to SQL-standard

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More resources
Apache ImpalaFatDBHazelcastIBM Db2 Event Store
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