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DBMS > Apache Druid vs. HyperSQL vs. Microsoft Azure Data Explorer vs. Oracle NoSQL vs. TimescaleDB

System Properties Comparison Apache Druid vs. HyperSQL vs. Microsoft Azure Data Explorer vs. Oracle NoSQL vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle NoSQL  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataMultithreaded, transactional RDBMS written in Java infoalso known as HSQLDBFully managed big data interactive analytics platformA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMS infocolumn orientedDocument store
Key-value store
Relational DBMS
Time Series 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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.85
Rank#96  Overall
#50  Relational DBMS
#6  Time Series DBMS
Score3.14
Rank#85  Overall
#46  Relational DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score3.07
Rank#86  Overall
#15  Document stores
#11  Key-value stores
#47  Relational DBMS
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Websitedruid.apache.orghsqldb.orgazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­nosql/­technologies/­nosqlwww.timescale.com
Technical documentationdruid.apache.org/­docs/­latest/­designhsqldb.org/­web/­hsqlDocsFrame.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.htmldocs.timescale.com
DeveloperApache Software Foundation and contributorsMicrosoftOracleTimescale
Initial release20122001201920112017
Current release30.0.0, June 20242.7.2, June 2023cloud service with continuous releases24.1, May 20242.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infobased on BSD licensecommercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaC
Server operating systemsLinux
OS X
Unix
All OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modeshostedLinux
Solaris SPARC/x86
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesFixed schema with schema-less datatypes (dynamic)Support Fixed schema and Schema-less deployment with the ability to interoperate between them.yes
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-typesoptionalnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyesnoyes
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL for queryingyesKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HTTP API infoJDBC via HTTP
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBC
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoJava, SQLYes, possible languages: KQL, Python, Rnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneSharding infoImplicit feature of the cloud serviceShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Electable source-replica replication per shard. Support distributed global deployment with Multi-region table featureSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency infodepending on configuration
Immediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoconfigurable infoACID within a storage node (=shard)ACID
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.noyesnoyes infooff heap cacheno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardAzure Active Directory AuthenticationAccess rights for users and rolesfine grained access rights according to SQL-standard

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More resources
Apache DruidHyperSQL infoalso known as HSQLDBMicrosoft Azure Data ExplorerOracle NoSQLTimescaleDB
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