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DBMS > Apache Impala vs. DataFS vs. Microsoft Azure Table Storage vs. XTDB

System Properties Comparison Apache Impala vs. DataFS vs. Microsoft Azure Table Storage vs. XTDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDataFS  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.A 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 DBMSObject oriented DBMSWide column storeDocument store
Secondary database modelsDocument storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.11
Rank#343  Overall
#46  Document stores
Websiteimpala.apache.orgnewdatabase.comazure.microsoft.com/­en-us/­services/­storage/­tablesgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationimpala.apache.org/­impala-docs.htmldev.mobiland.com/­Overview.xspwww.xtdb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMobiland AGMicrosoftJuxt Ltd.
Initial release2013201820122019
Current release4.1.0, June 20221.1.263, October 20221.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen 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++Clojure
Server operating systemsLinuxWindowshostedAll OS with a Java 8 (and higher) VM
Linux
Data schemeyesClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-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 statementsnonolimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
.NET Client API
Proprietary client DLL
WinRT client
RESTful HTTP APIHTTP REST
JDBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
VB.Net
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenono
Triggersnono, except callback-events from server when changes happenednono
Partitioning methods infoMethods for storing different data on different nodesShardingProprietary Sharding systemSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes 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 ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, 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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosWindows-ProfileAccess rights based on private key authentication or shared access signatures

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More resources
Apache ImpalaDataFSMicrosoft Azure Table StorageXTDB infoformerly named Crux
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