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DBMS > Brytlyt vs. Drizzle vs. Impala vs. TimescaleDB

System Properties Comparison Brytlyt vs. Drizzle vs. Impala vs. TimescaleDB

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonDrizzle  Xexclude from comparisonImpala  Xexclude from comparisonTimescaleDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Analytic DBMS for HadoopA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.36
Rank#260  Overall
#121  Relational DBMS
Score18.71
Rank#38  Overall
#23  Relational DBMS
Score4.38
Rank#81  Overall
#5  Time Series DBMS
Websitewww.brytlyt.comwww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.htmlwww.timescale.com
Technical documentationdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.htmldocs.timescale.com
DeveloperBrytlytDrizzle project, originally started by Brian AkerClouderaTimescale
Initial release2016200820132017
Current release0.9, October 20167.2.4, September 20124.0.0, July 2021
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and CUDAC++C++C
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
OS X
LinuxLinux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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 indexesyesyesyesyes
SQL infoSupport of SQLyesyes infowith proprietary extensionsSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBCJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C
C++
Java
PHP
All languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLnoyes infouser defined functions and integration of map-reduceuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesno infohooks for callbacks inside the server can be used.noyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
selectable replication factorSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standard

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More resources
BrytlytDrizzleImpalaTimescaleDB
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Recent citations in the news

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
26 November 2021, PRNewswire

Brytlyt Unleashes Serverless GPU-Acceleration for Analytics
15 September 2021, PR Newswire UK

Brytlyt Awarded US Patent for Relational JOINs Algorithm
27 August 2021, PRNewswire

Brytlyt Lauded by Frost & Sullivan for Building BrytlytDB, a GPU-powered Analytics Platform that Is Transforming the Way Companies Leverage Data
21 June 2021, MarTech Series

Brytlyt Secures Series A to Turbocharge Real-Time Data Analytics
20 May 2020, PRNewswire

provided by Google News

Cloudera Boosts Hadoop App Development On Impala
10 November 2014, InformationWeek

Cloudera’s Impala brings Hadoop to SQL and BI
25 October 2012, ZDNet

Man Busts Out of Google, Rebuilds Top-Secret Query Machine
24 October 2012, Wired

Cloudera aims to bring real-time queries to Hadoop, big data
24 October 2012, ZDNet

Unravel Data Adds Native Support for Impala and Kafka
29 June 2017, insideBIGDATA

provided by Google News

Timescale grabs $40M Series B as it goes all in on cloud version of time series database
5 May 2021, TechCrunch

Understanding Hyperfunctions in TimescaleDB
11 August 2021, CDOTrends

Timescale launches the new Timescale Cloud, a hosted relational database for time-series
5 October 2021, Business Wire

Timescale scales out and sets its sights on analytics
17 June 2021, ZDNet

Timescale Launches Industry's First Multi-Node Relational Database for Time-Series Data, Giving Organizations Unprecedented Scale
29 October 2020, Business Wire

provided by Google News

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