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DBMS > Brytlyt vs. CrateDB vs. MySQL

System Properties Comparison Brytlyt vs. CrateDB vs. MySQL

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonCrateDB  Xexclude from comparisonMySQL  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLDistributed Database based on LuceneWidely used open source RDBMS
Primary database modelRelational DBMSDocument store
Time Series DBMS
Relational DBMS infoKey/Value like access via memcached API
Secondary database modelsRelational DBMS
Search engine
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.43
Rank#288  Overall
#131  Relational DBMS
Score0.82
Rank#237  Overall
#35  Document stores
#19  Time Series DBMS
Score1182.79
Rank#2  Overall
#2  Relational DBMS
Websitewww.brytlyt.comcrate.iowww.mysql.com
Technical documentationcrate.io/­-docsdev.mysql.com/­doc
DeveloperBrytlytCrateOracle infosince 2010, originally MySQL AB, then Sun
Initial release201620131995
Current release0.9, October 20168.0.32, January 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoGPL version 2. Commercial licenses with extended functionallity are available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
  • PlanetScale: Deploy a fully managed database with the reliability of MySQL and the scale of open source Vitess with PlanetScale today. Predictably scale, increase workflow velocity, and deploy features with zero downtime.
  • ScaleGrid for MySQL: Fully managed MySQL hosting On-Premises and on a wide variety of cloud providers. Easily deploy, monitor, provision, and scale your deployments in the cloud.
Implementation languageC, C++ and CUDAJavaC and C++
Server operating systemsLinux
OS X
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportFreeBSD
Linux
OS X
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yes
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 indexesyesyesyes
SQL infoSupport of SQLyesyes, but no triggers and constraints, and PostgreSQL compatibilityyes infowith proprietary extensions
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLuser defined functions (Javascript)yes infoproprietary syntax
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning, sharding with MySQL Cluster or MySQL Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationConfigurable replication on table/partition-levelMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate Consistency
Foreign keys infoReferential integrityyesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID infonot for MyISAM storage engine
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
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-standardrights management via user accountsUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
BrytlytCrateDBMySQL
Specific characteristicsCrateDB is an open-source distributed SQL database that spreads data and processing...
» more
Competitive advantagesCrateDB is typically used in operational analytics applications. In those scenarios,...
» more
Typical application scenariosCrateDB is ideal for integrating and analyzing streams of data in order to monitor,...
» more
Key customersCrateDB customers include Bitmovin , ALPLA , Gantner Instruments , SPGo! , TGW Logistics...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsCrateDB Cloud The efficiency & range of CrateDB in the Cloud CrateDB Edge brings...
» 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
BrytlytCrateDBMySQL
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Conferences and events

How O-CELL real-time monitoring solution helps to reduce the environmental impact of infrastructures with CrateDB
Webinar with Q&A; 5:00 pm - 5:45 pm CET, 5 April 2023

Learn simple No-Code Data Import and Visualization with CrateDB Cloud
Live Demo with Q&A; 4:00 pm - 4:30 pm CET, 27 April 2023

Finished events

Live Demo on Time-series data: from Raw Data to Fast Analysis in only 3 steps
Webinar, 16:00 - 16:45 CET, 22 February 2023 (finished)

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