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DBMS > Apache Druid vs. CrateDB vs. Microsoft Azure Data Explorer vs. openGauss vs. SwayDB

System Properties Comparison Apache Druid vs. CrateDB vs. Microsoft Azure Data Explorer vs. openGauss vs. SwayDB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonCrateDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonopenGauss  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDistributed Database based on LuceneFully managed big data interactive analytics platformAn enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by HuaweiAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMS
Time Series DBMS
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMS infocolumn orientedRelational DBMSKey-value store
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
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.06
Rank#184  Overall
#84  Relational DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Websitedruid.apache.orgcratedb.comazure.microsoft.com/­services/­data-explorergitee.com/­opengauss
opengauss.org
swaydb.simer.au
Technical documentationdruid.apache.org/­docs/­latest/­designcratedb.com/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.opengauss.org/­en
gitee.com/­opengauss/­docs
DeveloperApache Software Foundation and contributorsCrateMicrosoftHuawei and openGauss communitySimer Plaha
Initial release20122013201920192018
Current release29.0.1, April 2024cloud service with continuous releases3.0, March 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open SourcecommercialOpen SourceOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
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, C++, JavaScala
Server operating systemsLinux
OS X
Unix
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedLinux
Data schemeyes infoschema-less columns are supportedFlexible Schema (defined schema, partial schema, schema free)Fixed schema with schema-less datatypes (dynamic)yesschema-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-typesyesno
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.nonoyesnono
Secondary indexesyesyesall fields are automatically indexedyesno
SQL infoSupport of SQLSQL for queryingyes, but no triggers and constraints, and PostgreSQL compatibilityKusto Query Language (KQL), SQL subsetANSI SQL 2011no
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.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
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnouser defined functions (Javascript)Yes, possible languages: KQL, Python, Ryesno
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning (by range, list and hash)none
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesConfigurable replication on table/partition-levelyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategynoACIDAtomic execution of operations
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.nonononoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemrights management via user accountsAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standardno
More information provided by the system vendor
Apache DruidCrateDBMicrosoft Azure Data ExploreropenGaussSwayDB
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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Apache DruidCrateDBMicrosoft Azure Data ExploreropenGaussSwayDB
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