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DBMS > Apache Druid vs. Microsoft Azure Data Explorer vs. OceanBase vs. SwayDB vs. TimesTen

System Properties Comparison Apache Druid vs. Microsoft Azure Data Explorer vs. OceanBase vs. SwayDB vs. TimesTen

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOceanBase  Xexclude from comparisonSwayDB  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataFully managed big data interactive analytics platformA distributed, high available RDBMS compatible with Oracle and MySQLAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storageIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMS infocolumn orientedRelational DBMSKey-value storeRelational DBMS
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
Document store
Wide column store
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
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.57
Rank#149  Overall
#69  Relational DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitedruid.apache.orgazure.microsoft.com/­services/­data-exploreren.oceanbase.comswaydb.simer.auwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.microsoft.com/­en-us/­azure/­data-exploreren.oceanbase.com/­docs/­oceanbase-databasedocs.oracle.com/­database/­timesten-18.1
DeveloperApache Software Foundation and contributorsMicrosoftOceanBase infopreviously Alibaba and Ant GroupSimer PlahaOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20122019201020181998
Current release29.0.1, April 2024cloud service with continuous releases4.3.0, April 202411 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoCommercial license availableOpen Source infoGNU Affero GPL V3.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Scala
Server operating systemsLinux
OS X
Unix
hostedLinuxAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyes infoschema-less columns are supportedFixed schema with schema-less datatypes (dynamic)yesschema-freeyes
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-typesyesnoyes
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.noyesyesnono
Secondary indexesyesall fields are automatically indexedyesnoyes
SQL infoSupport of SQLSQL for queryingKusto Query Language (KQL), SQL subsetyesnoyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Ada infoin MySQL-compatible model
C infoin Oracle- and MySQL- compatible models
C++ infoin Oracle- and MySQL- compatible models
D infoin MySQL-compatible model
Delphi infoin MySQL-compatible model
Eiffel infoin MySQL-compatible model
Erlang infoin MySQL-compatible model
Haskell infoin MySQL-compatible model
Java infoin Oracle- and MySQL- compatible models
JavaScript (Node.js) infoin MySQL-compatible model
Objective-C infoin MySQL-compatible model
OCaml infoin MySQL-compatible model
Perl infoin MySQL-compatible model
PHP infoin MySQL-compatible model
Python infoin MySQL-compatible model
Ruby infoin MySQL-compatible model
Scheme infoin MySQL-compatible model
Tcl infoin MySQL-compatible model
Java
Kotlin
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RPL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible modenoPL/SQL
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoImplicit feature of the cloud servicehorizontal partitioning (by hash, key, range, range columns, list, and list columns)nonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication using PaxosnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDAtomic execution of operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
Apache DruidMicrosoft Azure Data ExplorerOceanBaseSwayDBTimesTen
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