DBMS > ClickHouse vs. Elasticsearch vs. Microsoft Azure Data Explorer vs. Sphinx vs. SQLite
System Properties Comparison ClickHouse vs. Elasticsearch vs. Microsoft Azure Data Explorer vs. Sphinx vs. SQLite
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Name | ClickHouse Xexclude from comparison | Elasticsearch Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Sphinx Xexclude from comparison | SQLite Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | A 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 distributed, RESTful modern search and analytics engine based on Apache Lucene Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric | Fully managed big data interactive analytics platform | Open source search engine for searching in data from different sources, e.g. relational databases | Widely used embeddable, in-process RDBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Search engine | Relational DBMS column oriented | Search engine | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Time Series DBMS | Document store Spatial DBMS Vector DBMS | Document store If 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 this 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 support 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 see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | clickhouse.com | www.elastic.co/elasticsearch | azure.microsoft.com/services/data-explorer | sphinxsearch.com | www.sqlite.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | clickhouse.com/docs | www.elastic.co/guide/en/elasticsearch/reference/current/index.html | docs.microsoft.com/en-us/azure/data-explorer | sphinxsearch.com/docs | www.sqlite.org/docs.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Clickhouse Inc. | Elastic | Microsoft | Sphinx Technologies Inc. | Dwayne Richard Hipp | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2016 | 2010 | 2019 | 2001 | 2000 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | v24.4.1.2088-stable, May 2024 | 8.6, January 2023 | cloud service with continuous releases | 3.5.1, February 2023 | 3.45.3 (15 April 2024), April 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache 2.0 | Open Source Elastic License | commercial | Open Source GPL version 2, commercial licence available | Open Source Public Domain | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C++ | Java | C++ | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | FreeBSD Linux macOS | All OS with a Java VM | hosted | FreeBSD Linux NetBSD OS X Solaris Windows | server-less | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | schema-free Flexible type definitions. Once a type is defined, it is persistent | Fixed schema with schema-less datatypes (dynamic) | yes | yes dynamic column types | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | no | yes not rigid because of 'dynamic typing' concept. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT. | no | no | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes All search fields are automatically indexed | all fields are automatically indexed | yes full-text index on all search fields | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | Close to ANSI SQL (SQL/JSON + extensions) | SQL-like query language | Kusto Query Language (KQL), SQL subset | SQL-like query language (SphinxQL) | yes SQL-92 is not fully supported | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | gRPC HTTP REST JDBC MySQL wire protocol ODBC PostgreSQL wire protocol Proprietary protocol | Java API RESTful HTTP/JSON API | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | Proprietary protocol | ADO.NET inofficial driver JDBC inofficial driver ODBC inofficial driver | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# 3rd party library C++ Elixir 3rd party library Go 3rd party library Java 3rd party library JavaScript (Node.js) 3rd party library Kotlin 3rd party library Nim 3rd party library Perl 3rd party library PHP 3rd party library Python 3rd party library R 3rd party library Ruby 3rd party library Rust Scala 3rd party library | .Net Groovy Community Contributed Clients Java JavaScript Perl PHP Python Ruby | .Net Go Java JavaScript (Node.js) PowerShell Python R | C++ unofficial client library Java Perl unofficial client library PHP Python Ruby unofficial client library | Actionscript Ada Basic C C# C++ D Delphi Forth Fortran Haskell Java JavaScript Lisp Lua MatLab Objective-C OCaml Perl PHP PL/SQL Python R Ruby Scala Scheme Smalltalk Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | yes | Yes, possible languages: KQL, Python, R | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes by using the 'percolation' feature | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | key based and custom | Sharding | Sharding Implicit feature of the cloud service | Sharding Partitioning is done manually, search queries against distributed index is supported | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages. | yes | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | none | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | ES-Hadoop Connector | Spark connector (open source): github.com/Azure/azure-kusto-spark | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual Consistency Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all | Eventual Consistency Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | no | no | no | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes via file-system locks | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes The original contents of fields are not stored in the Sphinx index. | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | Memcached and Redis integration | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | 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 Authentication | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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3rd parties | Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics. » more DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale. » more | Navicat for SQLite is a powerful and comprehensive SQLite GUI that provides a complete set of functions for database management and development. » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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ClickHouse | Elasticsearch | Microsoft Azure Data Explorer | Sphinx | SQLite | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | PostgreSQL is the DBMS of the Year 2017 Elasticsearch moved into the top 10 most popular database management systems MySQL, PostgreSQL and Redis are the winners of the March ranking | The DB-Engines ranking includes now search engines | Big gains for Relational Database Management Systems in DB-Engines Ranking Why Clickhouse Should Be Your Next Database ClickHouse Cloud & Amazon S3 Express One Zone: Making a blazing fast analytical database even faster | Amazon ... A 1000x Faster Database Solution: ClickHouse’s Aaron Katz ClickHouse Announces Launch of ClickPipes From Open Source to SaaS: the Journey of ClickHouse provided by Google News Elasticsearch Open Inference API Now Supports Microsoft Azure AI Studio Announcing Search AI Lake and Elastic Cloud Serverless to Scale Low Latency Search Elasticsearch Enables 400 Criteo Engineers to Search 4 TB of Log Data per Week Elasticsearch Delivers Performance Increase for Users Running the Elastic Search AI Platform on Arm-based ... Netflix Uses Elasticsearch Percolate Queries to Implement Reverse Searches Efficiently provided by Google News Azure Data Explorer: Log and telemetry analytics benchmark Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog Controlling costs in Azure Data Explorer using down-sampling and aggregation Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services Log and Telemetry Analytics Performance Benchmark provided by Google News Switching From Sphinx to MkDocs Documentation — What Did I Gain and Lose Manticore is a Faster Alternative to Elasticsearch in C++ Perplexity AI: From Its Use To Operation, Everything You Need To Know About Googles Newest Challenger The Pirate Bay was recently down for over a week due to a DDoS attack Beyond the Concert Hall: 5 Organizations Making a Difference in Classical Music in 2018 | WQXR Editorial provided by Google News A Guide to Working with SQLite Databases in Python How to work with Dapper and SQLite in ASP.NET Core SQLite's new support for binary JSON is similar but different from a PostgreSQL feature • DEVCLASS Universal API Access from Postgres and SQLite SQLite 3.44 Extends Aggregate Functions provided by Google News |
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