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DBMS > Brytlyt vs. HBase vs. Microsoft Access vs. Microsoft Azure Data Explorer vs. Sphinx

System Properties Comparison Brytlyt vs. HBase vs. Microsoft Access vs. Microsoft Azure Data Explorer vs. Sphinx

Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLWide-column store based on Apache Hadoop and on concepts of BigTableMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Fully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSWide column storeRelational DBMSRelational DBMS infocolumn orientedSearch engine
Secondary database modelsDocument 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
Score0.38
Rank#279  Overall
#126  Relational DBMS
Score31.25
Rank#26  Overall
#2  Wide column stores
Score105.40
Rank#11  Overall
#8  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Websitebrytlyt.iohbase.apache.orgwww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­services/­data-explorersphinxsearch.com
Technical documentationdocs.brytlyt.iohbase.apache.org/­book.htmldeveloper.microsoft.com/­en-us/­accessdocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docs
DeveloperBrytlytApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoftMicrosoftSphinx Technologies Inc.
Initial release20162008199220192001
Current release5.0, August 20232.3.4, January 20211902 (16.0.11328.20222), March 2019cloud service with continuous releases3.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercial infoBundled with Microsoft OfficecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and CUDAJavaC++C++
Server operating systemsLinux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
Windows infoNot a real database server, but making use of DLLshostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-free, schema definition possibleyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.yes infospecific XML-type available, but no XML query functionality.noyes
Secondary indexesyesnoyesall fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLyesnoyes infobut not compliant to any SQL standardKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP API
Thrift
ADO.NET
DAO
ODBC
OLE DB
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C
C#
C++
Groovy
Java
PHP
Python
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLyes infoCoprocessors in Javayes infosince Access 2010 using the ACE-engineYes, possible languages: KQL, Python, Rno
Triggersyesyesyes infosince Access 2010 using the ACE-engineyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
noneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)ACID infobut no files for transaction loggingnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno infoa simple user-level security was built in till version Access 2003Azure Active Directory Authenticationno

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More resources
BrytlytHBaseMicrosoft AccessMicrosoft Azure Data ExplorerSphinx
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