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

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

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Editorial information provided by DB-Engines
NameeXtremeDB  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionNatively in-memory DBMS with options for persistency, high-availability and clusteringTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platformCloud 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
Time Series DBMSRelational DBMS infocolumn orientedRelational 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
Score0.73
Rank#227  Overall
#104  Relational DBMS
#18  Time Series DBMS
Score0.57
Rank#250  Overall
#21  Time Series DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websitewww.mcobject.comgithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorerwww.vertica.com
Technical documentationwww.mcobject.com/­docs/­extremedb.htmspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorervertica.com/­documentation
DeveloperMcObjectSpotifyMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2001201420192005
Current release8.2, 2021cloud service with continuous releases12.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonoyesno 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++JavaC++
Server operating systemsAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedLinux
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)Yes, 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-typesyes
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 availablenoyesno
Secondary indexesyesyes infovia Elasticsearchall fields are automatically indexedNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyes infowith the option: eXtremeSQLnoKusto Query Language (KQL), SQL subsetFull 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
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP 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++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesnoYes, possible languages: KQL, Python, Ryes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infoby defining eventsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingShardingSharding 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
yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.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-sparkno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
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-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
eXtremeDBHeroicMicrosoft Azure Data ExplorerVertica 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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eXtremeDBHeroicMicrosoft Azure Data ExplorerVertica infoOpenText™ Vertica™
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