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DBMS > Apache Impala vs. IBM Db2 Event Store vs. Microsoft Azure Table Storage vs. XTDB

System Properties Comparison Apache Impala vs. IBM Db2 Event Store vs. Microsoft Azure Table Storage vs. XTDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDistributed Event Store optimized for Internet of Things use casesA Wide Column Store for rapid development using massive semi-structured datasetsA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSEvent Store
Time Series DBMS
Wide column storeDocument store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.11
Rank#343  Overall
#46  Document stores
Websiteimpala.apache.orgwww.ibm.com/­products/­db2-event-storeazure.microsoft.com/­en-us/­services/­storage/­tablesgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.ibm.com/­docs/­en/­db2-event-storewww.xtdb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaIBMMicrosoftJuxt Ltd.
Initial release2013201720122019
Current release4.1.0, June 20222.01.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree developer edition availablecommercialOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++Clojure
Server operating systemsLinuxLinux infoLinux, macOS, Windows for the developer additionhostedAll OS with a Java 8 (and higher) VM
Linux
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, extensible-data-notation format
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.nononono
Secondary indexesyesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infothrough the embedded Spark runtimenolimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIHTTP REST
JDBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorActive-active shard replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
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 Kerberosfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signatures

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More resources
Apache ImpalaIBM Db2 Event StoreMicrosoft Azure Table StorageXTDB infoformerly named Crux
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