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DBMS > CrateDB vs. Heroic vs. InterSystems Caché vs. Microsoft Azure Data Explorer vs. Microsoft Azure Synapse Analytics

System Properties Comparison CrateDB vs. Heroic vs. InterSystems Caché vs. Microsoft Azure Data Explorer vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonHeroic  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionDistributed Database based on LuceneTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA multi-model DBMS and application serverFully managed big data interactive analytics platformElastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Time Series DBMSKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMS infocolumn orientedRelational DBMS
Secondary database modelsRelational DBMSDocument storeDocument 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
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Websitecratedb.comgithub.com/­spotify/­heroicwww.intersystems.com/­products/­cacheazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­services/­synapse-analytics
Technical documentationcratedb.com/­docsspotify.github.io/­heroicdocs.intersystems.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.microsoft.com/­azure/­synapse-analytics
DeveloperCrateSpotifyInterSystemsMicrosoftMicrosoft
Initial release20132014199720192016
Current release2018.1.4, May 2020cloud service with continuous releases
License infoCommercial or Open SourceOpen SourceOpen Source infoApache 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
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 supportAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
hostedhosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freedepending on used data modelFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyesyes 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.nonoyesyesno
Secondary indexesyesyes infovia Elasticsearchyesall fields are automatically indexedyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoyesKusto Query Language (KQL), SQL subsetyes
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
.NET Client API
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
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#
C++
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
Java
PHP
Server-side scripts infoStored proceduresuser defined functions (Javascript)noyesYes, possible languages: KQL, Python, RTransact SQL
Triggersnonoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoImplicit feature of the cloud serviceSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelyesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
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 infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
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 strategynoACIDnoACID
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.nonoyesno
User concepts infoAccess controlrights management via user accountsAccess rights for users, groups and rolesAzure Active Directory Authenticationyes
More information provided by the system vendor
CrateDBHeroicInterSystems CachéMicrosoft Azure Data ExplorerMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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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CrateDBHeroicInterSystems CachéMicrosoft Azure Data ExplorerMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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