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DBMS > HBase vs. Manticore Search vs. Microsoft Azure Data Explorer vs. Netezza

System Properties Comparison HBase vs. Manticore Search vs. Microsoft Azure Data Explorer vs. Netezza

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Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionWide-column store based on Apache Hadoop and on concepts of BigTableMulti-storage database for search, including full-text search.Fully managed big data interactive analytics platformData warehouse and analytics appliance part of IBM PureSystems
Primary database modelWide column storeSearch engineRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsTime Series DBMS infousing the Manticore Columnar LibraryDocument 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
Score27.97
Rank#26  Overall
#2  Wide column stores
Score0.29
Rank#302  Overall
#21  Search engines
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websitehbase.apache.orgmanticoresearch.comazure.microsoft.com/­services/­data-explorerwww.ibm.com/­products/­netezza
Technical documentationhbase.apache.org/­book.htmlmanual.manticoresearch.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetManticore SoftwareMicrosoftIBM
Initial release2008201720192000
Current release2.3.4, January 20216.0, February 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache version 2Open Source infoGPL version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemsLinux
Unix
Windows infousing Cygwin
FreeBSD
Linux
macOS
Windows
hostedLinux infoincluded in appliance
Data schemeschema-free, schema definition possibleFixed schemaFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.noCan index from XMLyes
Secondary indexesnoyes infofull-text index on all search fieldsall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like query languageKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJava API
RESTful HTTP API
Thrift
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresyes infoCoprocessors in Javauser defined functionsYes, possible languages: KQL, Python, Ryes
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Synchronous replication based on Galera libraryyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)yes infoisolated transactions for atomic changes and binary logging for safe writesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Manticore index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnoAzure Active Directory AuthenticationUsers with fine-grained authorization concept

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More resources
HBaseManticore SearchMicrosoft Azure Data ExplorerNetezza infoAlso called PureData System for Analytics by IBM
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