DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon Neptune vs. ClickHouse vs. Microsoft Azure Data Explorer vs. SwayDB

System Properties Comparison Amazon Neptune vs. ClickHouse vs. Microsoft Azure Data Explorer vs. SwayDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonClickHouse  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA 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.Fully managed big data interactive analytics platformAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMS infocolumn orientedKey-value store
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score16.34
Rank#38  Overall
#23  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websiteaws.amazon.com/­neptuneclickhouse.comazure.microsoft.com/­services/­data-explorerswaydb.simer.au
Technical documentationaws.amazon.com/­neptune/­developer-resourcesclickhouse.com/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAmazonClickhouse Inc.MicrosoftSimer Plaha
Initial release2017201620192018
Current releasev24.4.1.2088-stable, May 2024cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
  • Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
  • 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.
Implementation languageC++Scala
Server operating systemshostedFreeBSD
Linux
macOS
hosted
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)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-typesno
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 indexesnoyesall fields are automatically indexedno
SQL infoSupport of SQLnoClose to ANSI SQL (SQL/JSON + extensions)Kusto Query Language (KQL), SQL subsetno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C# 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
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnoyesYes, possible languages: KQL, Python, Rno
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesnonekey based and customSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access 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.Azure Active Directory Authenticationno

More information provided by the system vendor

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
Amazon NeptuneClickHouseMicrosoft Azure Data ExplorerSwayDB
Recent citations in the news

Amazon Neptune Analytics is now available in the AWS Europe (London) Region
14 March 2024, AWS Blog

Amazon Neptune Analytics is now generally available
29 November 2023, AWS Blog

Find and link similar entities in a knowledge graph using Amazon Neptune, Part 1: Full-text search | Amazon Web ...
7 May 2024, AWS Blog

Find and link similar entities in a knowledge graph using Amazon Neptune, Part 2: Vector similarity search | Amazon ...
7 May 2024, AWS Blog

Analyze large amounts of graph data to get insights and find trends with Amazon Neptune Analytics | Amazon Web ...
29 November 2023, AWS Blog

provided by Google News

Ubuntu 24.04 + Linux 6.9 Intel & AMD Server Performance
23 May 2024, Phoronix

Why Clickhouse Should Be Your Next Database
6 July 2023, The New Stack

ClickHouse Cloud & Amazon S3 Express One Zone: Making a blazing fast analytical database even faster | Amazon ...
28 November 2023, AWS Blog

ClickHouse Announces Launch of ClickPipes
26 September 2023, Datanami

From Open Source to SaaS: the Journey of ClickHouse
16 January 2024, InfoQ.com

provided by Google News

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, Microsoft

Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog
13 July 2023, microsoft.com

Microsoft Introduces Azure Integration Environments and Business Process Tracking in Public Preview
23 November 2023, InfoQ.com

Controlling costs in Azure Data Explorer using down-sampling and aggregation
11 February 2019, Microsoft

Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services
7 February 2019, Microsoft

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

SingleStore logo

The database to transact, analyze and contextualize your data in real time.
Try it today.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here