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DBMS > Blueflood vs. Brytlyt vs. Microsoft Azure Data Explorer vs. Teradata Aster vs. Trino

System Properties Comparison Blueflood vs. Brytlyt vs. Microsoft Azure Data Explorer vs. Teradata Aster vs. Trino

Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonBrytlyt  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTrino  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionScalable TimeSeries DBMS based on CassandraScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLFully managed big data interactive analytics platformPlatform for big data analytics on multistructured data sources and typesFast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL
Primary database modelTime Series DBMSRelational DBMSRelational DBMS infocolumn orientedRelational DBMSRelational 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)
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
Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#346  Overall
#33  Time Series DBMS
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.99
Rank#65  Overall
#36  Relational DBMS
Websiteblueflood.iobrytlyt.ioazure.microsoft.com/­services/­data-explorertrino.io
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.brytlyt.iodocs.microsoft.com/­en-us/­azure/­data-explorertrino.io/­broadcast
trino.io/­docs/­current
Social network pagesLinkedInTwitterYouTubeGitHub
DeveloperRackspaceBrytlytMicrosoftTeradataTrino Software Foundation
Initial release20132016201920052012 info2020 rebranded from PrestoSQL
Current release5.0, August 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.
Implementation languageJavaC, C++ and CUDAJava
Server operating systemsLinux
OS X
Linux
OS X
Windows
hostedLinuxLinux
macOS infofor devlopment
Data schemepredefined schemeyesFixed schema with schema-less datatypes (dynamic)Flexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.noyes infospecific XML-type available, but no XML query functionality.yesyes infoin Aster File Storeno
Secondary indexesnoyesall fields are automatically indexedyesdepending on connected data-source
SQL infoSupport of SQLnoyesKusto Query Language (KQL), SQL subsetyesyes
APIs and other access methodsHTTP RESTADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
JDBC
RESTful HTTP API
Trino CLI
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Java
Python
R
Go
Java
JavaScript (Node.js)
Python
R
Ruby
Server-side scripts infoStored proceduresnouser defined functions infoin PL/pgSQLYes, possible languages: KQL, Python, RR packagesyes, depending on connected data-source
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding infoImplicit feature of the cloud serviceShardingdepending on connected data-source
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.depending on connected data-source
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationdepending on connected data-source
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDdepending on connected data-source
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesdepending on connected data-source
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlnofine grained access rights according to SQL-standardAzure Active Directory Authenticationfine grained access rights according to SQL-standardSQL standard access control
More information provided by the system vendor
BluefloodBrytlytMicrosoft Azure Data ExplorerTeradata AsterTrino
Specific characteristicsTrino is the fastest open source, massively parallel processing SQL query engine...
» more
Competitive advantagesHigh performance analtyics and data processing of very large data sets Powerful ANSI...
» more
Typical application scenariosPerformant analytics query engine for data warehouses, data lakes, and data lakehouses...
» more
Key customersTrino is widely adopted across the globe as freely-available open source software....
» more
Market metrics33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
» more
Licensing and pricing modelsTrino is an open source project and usage is therefore free. Commercial offerings...
» more
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BluefloodBrytlytMicrosoft Azure Data ExplorerTeradata AsterTrino
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