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DBMS > eXtremeDB vs. Microsoft Azure Data Explorer vs. Transbase vs. Vertica

System Properties Comparison eXtremeDB vs. Microsoft Azure Data Explorer vs. Transbase vs. Vertica

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Editorial information provided by DB-Engines
NameeXtremeDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTransbase  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionNatively in-memory DBMS with options for persistency, high-availability and clusteringFully managed big data interactive analytics platformA resource-optimized, high-performance, universally applicable RDBMSCloud 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 modelRelational DBMS
Time Series DBMS
Relational 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
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitewww.mcobject.comazure.microsoft.com/­services/­data-explorerwww.transaction.de/­en/­products/­transbase.htmlwww.vertica.com
Technical documentationwww.mcobject.com/­docs/­extremedb.htmdocs.microsoft.com/­en-us/­azure/­data-explorerwww.transaction.de/­en/­products/­transbase/­features.htmlvertica.com/­documentation
DeveloperMcObjectMicrosoftTransaction Software GmbHOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2001201919872005
Current release8.2, 2021cloud service with continuous releasesTransbase 8.3, 202212.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree development licensecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C and C++C++
Server operating systemsAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedFreeBSD
Linux
macOS
Solaris
Windows
Linux
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesYes, 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 dateyesyes 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.no infosupport of XML interfaces availableyesnono
Secondary indexesyesall fields are automatically indexedyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyes infowith the option: eXtremeSQLKusto Query Language (KQL), SQL subsetyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methods.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary native API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Ryesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infoby defining eventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingSharding infoImplicit feature of the cloud servicehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationMulti-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 methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyesACID
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyes
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.yesnonono
User concepts infoAccess controlAzure 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
eXtremeDBMicrosoft Azure Data ExplorerTransbaseVertica infoOpenText™ Vertica™
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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Cost-based models and subscription-based models are both available. One license is...
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eXtremeDBMicrosoft Azure Data ExplorerTransbaseVertica infoOpenText™ Vertica™
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