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DBMS > Apache Druid vs. DolphinDB vs. Microsoft Azure Data Explorer vs. SingleStore vs. SpatiaLite

System Properties Comparison Apache Druid vs. DolphinDB vs. Microsoft Azure Data Explorer vs. SingleStore vs. SpatiaLite

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDolphinDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonSpatiaLite  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.Fully managed big data interactive analytics platformMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typeSpatial extension of SQLite
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSRelational DBMS infocolumn orientedRelational DBMSSpatial DBMS
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
Time Series DBMS
Vector DBMS
Relational 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
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score5.38
Rank#62  Overall
#35  Relational DBMS
Score1.63
Rank#146  Overall
#3  Spatial DBMS
Websitedruid.apache.orgwww.dolphindb.comazure.microsoft.com/­services/­data-explorerwww.singlestore.comwww.gaia-gis.it/­fossil/­libspatialite/­index
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.dolphindb.cn/­en/­help200/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.singlestore.comwww.gaia-gis.it/­gaia-sins/­spatialite_topics.html
DeveloperApache Software Foundation and contributorsDolphinDB, IncMicrosoftSingleStore Inc.Alessandro Furieri
Initial release20122018201920132008
Current release29.0.1, April 2024v2.00.4, January 2022cloud service with continuous releases8.5, January 20245.0.0, August 2020
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree community version availablecommercialcommercial infofree developer edition availableOpen Source infoMPL 1.1, GPL v2.0 or LGPL v2.1
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.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageJavaC++C++, GoC++
Server operating systemsLinux
OS X
Unix
Linux
Windows
hostedLinux info64 bit version requiredserver-less
Data schemeyes infoschema-less columns are supportedyesFixed schema with schema-less datatypes (dynamic)yesyes
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-typesyesyes
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 indexedyesyes
SQL infoSupport of SQLSQL for queryingSQL-like query languageKusto Query Language (KQL), SQL subsetyes infobut no triggers and foreign keysyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyesYes, possible languages: KQL, Python, Ryesno
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioningSharding infoImplicit feature of the cloud serviceSharding infohash partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infostores two copies of each physical data partition on two separate nodesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocan define user-defined aggregate functions for map-reduce-style calculationsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAdministrators, Users, GroupsAzure Active Directory AuthenticationFine grained access control via users, groups and rolesno
More information provided by the system vendor
Apache DruidDolphinDBMicrosoft Azure Data ExplorerSingleStore infoformer name was MemSQLSpatiaLite
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

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More resources
Apache DruidDolphinDBMicrosoft Azure Data ExplorerSingleStore infoformer name was MemSQLSpatiaLite
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