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

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

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 comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
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 nodesAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMS infocolumn orientedDocument store
Key-value store
Relational DBMS
Document store
Graph DBMS
Key-value store
Wide column store
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
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
Websitedruid.apache.orghsqldb.orgazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­nosql/­technologies/­nosqlsqrrl.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.html
DeveloperApache Software Foundation and contributorsMicrosoftOracleAmazon infooriginally Sqrrl Data, Inc.
Initial release20122001201920112012
Current release30.0.0, June 20242.7.2, June 2023cloud service with continuous releases24.1, 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)commercial
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.
Implementation languageJavaJavaJavaJava
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
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.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-typesoptionalyes
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.nonoyesno
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL for queryingyesKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statementsno
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 APIAccumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
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
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoJava, SQLYes, possible languages: KQL, Python, Rnono
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneSharding infoImplicit feature of the cloud serviceShardingSharding infomaking use of Hadoop
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 featureselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency infodepending on configuration
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoconfigurable infoACID within a storage node (=shard)Atomic updates per row, document, or graph entity
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 cache
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 rolesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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