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DBMS > CrateDB vs. Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer vs. searchxml

System Properties Comparison CrateDB vs. Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer vs. searchxml

Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonHeroic  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonsearchxml  Xexclude from comparison
DescriptionDistributed Database based on LuceneTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesFully managed big data interactive analytics platformDBMS for structured and unstructured content wrapped with an application server
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Time Series DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedNative XML DBMS
Search engine
Secondary database modelsRelational DBMSDocument 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.03
Rank#390  Overall
#7  Native XML DBMS
#24  Search engines
Websitecratedb.comgithub.com/­spotify/­heroicwww.leanxcale.comazure.microsoft.com/­services/­data-explorerwww.searchxml.net/­category/­products
Technical documentationcratedb.com/­docsspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorerwww.searchxml.net/­support/­handouts
DeveloperCrateSpotifyLeanXcaleMicrosoftinformationpartners gmbh
Initial release20132014201520192015
Current releasecloud service with continuous releases1.0
License infoCommercial or Open SourceOpen SourceOpen Source infoApache 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJavaC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedWindows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesFixed schema with schema-less datatypes (dynamic)schema-free
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.nonoyesyes
Secondary indexesyesyes infovia Elasticsearchall fields are automatically indexedyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoyes infothrough Apache DerbyKusto Query Language (KQL), SQL subsetno
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
WebDAV
XQuery
XSLT
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infomost other programming languages supported via APIs
Server-side scripts infoStored proceduresuser defined functions (Javascript)noYes, possible languages: KQL, Python, Ryes infoon the application server
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infosychronisation to multiple collections
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategynoACIDnomultiple readers, single writer
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.nonoyesnono
User concepts infoAccess controlrights management via user accountsAzure Active Directory AuthenticationDomain, group and role-based access control at the document level and for application services
More information provided by the system vendor
CrateDBHeroicLeanXcaleMicrosoft Azure Data Explorersearchxml
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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More resources
CrateDBHeroicLeanXcaleMicrosoft Azure Data Explorersearchxml
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