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DBMS > ClickHouse vs. HugeGraph vs. Microsoft Azure Data Explorer vs. Sadas Engine vs. Trino

System Properties Comparison ClickHouse vs. HugeGraph vs. Microsoft Azure Data Explorer vs. Sadas Engine vs. Trino

Editorial information provided by DB-Engines
NameClickHouse  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSadas Engine  Xexclude from comparisonTrino  Xexclude from comparison
DescriptionA high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.A fast-speed and highly-scalable Graph DBMSFully managed big data interactive analytics platformSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsFast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL
Primary database modelRelational DBMSGraph DBMSRelational DBMS infocolumn orientedRelational DBMSRelational DBMS
Secondary database modelsTime Series 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
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score15.55
Rank#38  Overall
#23  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score4.99
Rank#65  Overall
#36  Relational DBMS
Websiteclickhouse.comgithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­services/­data-explorerwww.sadasengine.comtrino.io
Technical documentationclickhouse.com/­docshugegraph.apache.org/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationtrino.io/­broadcast
trino.io/­docs/­current
Social network pagesLinkedInTwitterYouTubeGitHub
DeveloperClickhouse Inc.BaiduMicrosoftSADAS s.r.l.Trino Software Foundation
Initial release20162018201920062012 info2020 rebranded from PrestoSQL
Current releasev24.4.1.2088-stable, May 20240.9cloud service with continuous releases8.0
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0commercialcommercial infofree trial version availableOpen Source infoApache Version 2.0
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.
  • DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
  • ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
  • Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.
Implementation languageC++JavaC++Java
Server operating systemsFreeBSD
Linux
macOS
Linux
macOS
Unix
hostedAIX
Linux
Windows
Linux
macOS infofor devlopment
Data schemeyesyesFixed 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 indexesyesyes infoalso supports composite index and range indexall fields are automatically indexedyesdepending on connected data-source
SQL infoSupport of SQLClose to ANSI SQL (SQL/JSON + extensions)noKusto Query Language (KQL), SQL subsetyesyes
APIs and other access methodsgRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
Java API
RESTful HTTP API
TinkerPop Gremlin
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
JDBC
RESTful HTTP API
Trino CLI
Supported programming languagesC# info3rd party library
C++
Elixir info3rd party library
Go info3rd party library
Java info3rd party library
JavaScript (Node.js) info3rd party library
Kotlin info3rd party library
Nim info3rd party library
Perl info3rd party library
PHP info3rd party library
Python info3rd party library
R info3rd party library
Ruby info3rd party library
Rust
Scala info3rd party library
Groovy
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Groovy
Java
PHP
Python
Go
Java
JavaScript (Node.js)
Python
R
Ruby
Server-side scripts infoStored proceduresyesasynchronous Gremlin script jobsYes, possible languages: KQL, Python, Rnoyes, depending on connected data-source
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodeskey based and customyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud servicehorizontal partitioningdepending on connected data-source
Replication methods infoMethods for redundantly storing data on multiple nodesAsynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.yes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.nonedepending on connected data-source
MapReduce infoOffers an API for user-defined Map/Reduce methodsnovia hugegraph-sparkSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistencydepending on connected data-source
Foreign keys infoReferential integritynoyes infoedges in graphnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnodepending on connected data-source
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesdepending on connected data-source
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.Users, roles and permissionsAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standardSQL standard access control
More information provided by the system vendor
ClickHouseHugeGraphMicrosoft Azure Data ExplorerSadas EngineTrino
Specific characteristicsTrino is the fastest open source, massively parallel processing SQL query engine...
» more
Competitive advantagesHigh performance analtyics and data processing of very large data sets Powerful ANSI...
» more
Typical application scenariosPerformant analytics query engine for data warehouses, data lakes, and data lakehouses...
» more
Key customersTrino is widely adopted across the globe as freely-available open source software....
» more
Market metrics33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
» more
Licensing and pricing modelsTrino is an open source project and usage is therefore free. Commercial offerings...
» more
News

One busy week to go before Trino Fest 2024
6 June 2024

60: Trino calling AI
22 May 2024

Big names round out the Trino Fest 2024 lineup
8 May 2024

59: Querying Trino with Java and jOOQ
24 April 2024

A sneak peek of Trino Fest 2024
15 April 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services
3rd partiesDoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
» more

Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
ClickHouseHugeGraphMicrosoft Azure Data ExplorerSadas EngineTrino
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