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

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

Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonBrytlyt  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTeradata Aster  Xexclude from comparisonVertica infoOpenText™ Vertica™  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 typesCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelTime Series DBMSRelational DBMSRelational DBMS infocolumn orientedRelational DBMSRelational DBMS infoColumn oriented
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
Spatial DBMS
Time Series DBMS
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
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiteblueflood.iobrytlyt.ioazure.microsoft.com/­services/­data-explorerwww.vertica.com
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.brytlyt.iodocs.microsoft.com/­en-us/­azure/­data-explorervertica.com/­documentation
DeveloperRackspaceBrytlytMicrosoftTeradataOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20132016201920052005
Current release5.0, August 2023cloud service with continuous releases12.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonoyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++ and CUDAC++
Server operating systemsLinux
OS X
Linux
OS X
Windows
hostedLinuxLinux
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, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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 indexedyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoyesKusto Query Language (KQL), SQL subsetyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
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
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
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
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnouser defined functions infoin PL/pgSQLYes, possible languages: KQL, Python, RR packagesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioning, hierarchical partitioning
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.Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes infoSQL Map-Reduce Frameworkno infoBi-directional Spark integration
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 configurationImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlnofine grained access rights according to SQL-standardAzure Active Directory Authenticationfine 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
BluefloodBrytlytMicrosoft Azure Data ExplorerTeradata AsterVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
BluefloodBrytlytMicrosoft Azure Data ExplorerTeradata AsterVertica infoOpenText™ Vertica™
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