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DBMS > Dolt vs. Microsoft Azure Data Explorer vs. QuestDB vs. Sphinx

System Properties Comparison Dolt vs. Microsoft Azure Data Explorer vs. QuestDB vs. Sphinx

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Editorial information provided by DB-Engines
NameDolt  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA MySQL compatible DBMS with Git-like versioning of data and schemaFully managed big data interactive analytics platformA high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMS infocolumn orientedTime Series DBMSSearch engine
Secondary database modelsDocument storeDocument 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
Score0.96
Rank#193  Overall
#90  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitegithub.com/­dolthub/­dolt
www.dolthub.com
azure.microsoft.com/­services/­data-explorerquestdb.iosphinxsearch.com
Technical documentationdocs.dolthub.comdocs.microsoft.com/­en-us/­azure/­data-explorerquestdb.io/­docssphinxsearch.com/­docs
DeveloperDoltHub IncMicrosoftQuestDB Technology IncSphinx Technologies Inc.
Initial release2018201920142001
Current releasecloud service with continuous releases3.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava (Zero-GC), C++, RustC++
Server operating systemsLinux
macOS
Windows
hostedLinux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)yes infoschema-free via InfluxDB Line Protocolyes
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-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.noyesno
Secondary indexesyesall fields are automatically indexednoyes infofull-text index on all search fields
SQL infoSupport of SQLyesKusto Query Language (KQL), SQL subsetSQL with time-series extensionsSQL-like query language (SphinxQL)
APIs and other access methodsCLI Client
HTTP REST
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Proprietary protocol
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infocurrently in alpha releaseYes, possible languages: KQL, Python, Rnono
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud servicehorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesA database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infothrough memory mapped files
User concepts infoAccess controlOnly one user is configurable, and must be specified in the config file at startupAzure Active Directory Authenticationno
More information provided by the system vendor
DoltMicrosoft Azure Data ExplorerQuestDBSphinx
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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