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DBMS > Brytlyt vs. OmniSci vs. Vertica

System Properties Comparison Brytlyt vs. OmniSci vs. Vertica

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLA high performance, in-memory, column-oriented RDBMS, designed to run on GPUsColumnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.44
Rank#242  Overall
#115  Relational DBMS
Score1.24
Rank#151  Overall
#72  Relational DBMS
Score20.40
Rank#34  Overall
#20  Relational DBMS
Websitewww.brytlyt.comwww.omnisci.comwww.vertica.com
Technical documentationdocs.omnisci.comwww.vertica.com/­docs/­10.0.x/­HTML/­Content/­Home.htm
DeveloperBrytlytMapD Technologies, Inc.Vertica / Micro Focus infoprior to that Hewlett Packard
Initial release201620162005
Current release0.9, October 20165.5, January 2021Vertica 10.0 Software, May 2020
Vertica for SQL on Hadoop 10.0 Software, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoAvailable on all major clouds - Amazon AWS, Microsoft Azure and Google Cloud Platform
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
LinuxLinux
Data schemeyesyesyes infoUnstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesnono infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLyesyesyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Thrift
ADO.NET
JDBC
Kafka
ODBC
Proprietary protocol
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
Perl
Python
R
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLnoyes
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinSharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationMulti-source replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
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.yes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
BrytlytOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018Vertica infoVertica Analytics Platform
Specific characteristicsColumnar storage, MPP, Hybrid storage model, Aggressive data compression, High availability,...
» more
Competitive advantagesPerformance at exabyte scale, Deploy anywhere, Open source innovation, Analysis in...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are available
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
BrytlytOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018Vertica infoVertica Analytics Platform
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