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DBMS > Brytlyt vs. Microsoft Azure Data Explorer vs. OmniSci

System Properties Comparison Brytlyt vs. Microsoft Azure Data Explorer vs. OmniSci

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLFully managed big data interactive analytics platformA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware
Primary database modelRelational DBMSRelational DBMS infocolumn orientedRelational DBMS
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)
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
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#253  Overall
#118  Relational DBMS
Score6.59
Rank#60  Overall
#34  Relational DBMS
Score1.27
Rank#153  Overall
#73  Relational DBMS
Websitewww.brytlyt.comazure.microsoft.com/­services/­data-explorergithub.com/­omnisci/­omniscidb
www.omnisci.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.omnisci.com
DeveloperBrytlytMicrosoftMapD Technologies, Inc.
Initial release201620192016
Current release0.9, October 2016cloud service with continuous releases5.10, January 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and CUDAC++ and CUDA
Server operating systemsLinux
OS X
Windows
hostedLinux
Data schemeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes 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.yes infospecific XML-type available, but no XML query functionality.yesno
Secondary indexesyesall fields are automatically indexedno
SQL infoSupport of SQLyesKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLYes, possible languages: KQL, Python, Rno
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
BrytlytMicrosoft Azure Data ExplorerOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018
Specific characteristicsAzure Data Explorer is a fast and highly scalable data exploration service for log...
» more
Optimizes memory and compute layers to deliver unprecedented performance. Natively...
» more
Competitive advantagesKusto Query Language (innovative query language, optimized for high performance data...
» more
Only OmniSci allows users to visually and interactively discover high-value patterns,...
» more
Typical application scenariosIoT applications IoT devices generate billions of sensor readings. Normalizing and...
» more
Spatiotemporal and interactive visual analysis on massive, disparate datasets.
» more
Key customersMicrosoft, DocuSign, Taboola, Bosch, Siemens Healthineers, Bühler, Ecolab, Zoomd
» more
Market metricsAzure Data Explorer is the data service for Azure Monitor, Azure Time Series Insights,...
» more
Licensing and pricing modelsOmniSci Free (Free Forever), Foundations ($2k/month), and Enterprise Licensure (Inquire...
» more

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BrytlytMicrosoft Azure Data ExplorerOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018
Recent citations in the news

GPU-accelerated data analytics startup Brytlyt raises $5M
22 December 2021, SiliconANGLE News

Global GPU Database Market 2021 – Industry Developments, Outlook, Current Trends by 2027 – Discovery Sports Media
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Brytlyt Secures Series A to Turbocharge Real-Time Data Analytics
20 May 2020, PRNewswire

USD 361.56 million growth for GPU Database Market from 2020 to 2025 |Evolving Opportunities with BlazingSQL Inc., Brytlyt Ltd. & Hetero DB Co. Ltd.|17000+ Technavio Reports
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Global GPU Database Market 2021 – Industry Developments, Outlook, Current Trends by 2027 – Discovery Sports Media
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Review: OmniSci GPU database lifts huge data sets
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The Global GPU Database Market is expected to grow by $ 361.56 mn during 2021-2025, progressing at a CAGR of 17.82% during the forecast period
21 December 2021, Yahoo Finance

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