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DBMS > Apache Impala vs. HBase vs. Microsoft Azure Data Explorer vs. Riak KV vs. STSdb

System Properties Comparison Apache Impala vs. HBase vs. Microsoft Azure Data Explorer vs. Riak KV vs. STSdb

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRiak KV  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopWide-column store based on Apache Hadoop and on concepts of BigTableFully managed big data interactive analytics platformDistributed, fault tolerant key-value storeKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSWide column storeRelational DBMS infocolumn orientedKey-value store infowith links between data sets and object tags for the creation of secondary indexesKey-value store
Secondary database modelsDocument storeDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score0.04
Rank#360  Overall
#52  Key-value stores
Websiteimpala.apache.orghbase.apache.orgazure.microsoft.com/­services/­data-explorergithub.com/­STSSoft/­STSdb4
Technical documentationimpala.apache.org/­impala-docs.htmlhbase.apache.org/­book.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoftOpenSource, formerly Basho TechnologiesSTS Soft SC
Initial release20132008201920092011
Current release4.1.0, June 20222.3.4, January 2021cloud service with continuous releases3.2.0, December 20224.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache version 2commercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaErlangC#
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
hostedLinux
OS X
Windows
Data schemeyesschema-free, schema definition possibleFixed schema with schema-less datatypes (dynamic)schema-freeyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoyes infoprimitive types and user defined types (classes)
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.nonoyesno
Secondary indexesyesnoall fields are automatically indexedrestrictedno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
.NET Client API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C#
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoCoprocessors in JavaYes, possible languages: KQL, Python, RErlangno
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"none
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynononono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)nonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
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 KerberosAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAzure Active Directory Authenticationyes, using Riak Securityno

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More resources
Apache ImpalaHBaseMicrosoft Azure Data ExplorerRiak KVSTSdb
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