DBMS > Amazon Aurora vs. ClickHouse vs. CrateDB vs. InfluxDB vs. MySQL
System Properties Comparison Amazon Aurora vs. ClickHouse vs. CrateDB vs. InfluxDB vs. MySQL
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| Name | Amazon Aurora Xexclude from comparison | ClickHouse Xexclude from comparison | CrateDB Xexclude from comparison | InfluxDB Xexclude from comparison | MySQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | MySQL and PostgreSQL compatible cloud service by Amazon | 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. | Distributed Database based on Lucene | DBMS for storing time series, events and metrics | Widely used open source RDBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Relational DBMS | Relational DBMS | Document store Spatial DBMS Search engine Time Series DBMS Vector DBMS | Time Series DBMS | Relational DBMS  Key/Value like access via memcached API | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Document store | Time Series DBMS | Relational DBMS | Spatial DBMS with GEO package | Document store Spatial DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | aws.amazon.com/rds/aurora | clickhouse.com | cratedb.com | www.influxdata.com/products/influxdb-overview | www.mysql.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html | clickhouse.com/docs | cratedb.com/docs | docs.influxdata.com/influxdb | dev.mysql.com/doc | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Amazon | Clickhouse Inc. | Crate | Oracle since 2010, originally MySQL AB, then Sun | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2015 | 2016 | 2013 | 2013 | 1995 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | v23.12.1.1368-stable, December 2023 | 2.7.5, January 2024 | 8.3.0, January 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | Open Source Apache 2.0 | Open Source | Open Source MIT-License; commercial enterprise version available | Open Source GPL version 2. Commercial licenses with extended functionallity are available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. |
| CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform. | Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | C++ | Java | Go | C and C++ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | hosted | FreeBSD Linux macOS | All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support | Linux OS X through Homebrew | FreeBSD Linux OS X Solaris Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | yes | Flexible Schema (defined schema, partial schema, schema free) | schema-free | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes | yes | Numeric data and Strings | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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. | yes | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | yes | Close to ANSI SQL (SQL/JSON + extensions) | yes, but no triggers and constraints, and PostgreSQL compatibility | SQL-like query language | yes with proprietary extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | ADO.NET JDBC ODBC | gRPC HTTP REST JDBC MySQL wire protocol ODBC PostgreSQL wire protocol Proprietary protocol | ADO.NET JDBC ODBC PostgreSQL wire protocol Prometheus Remote Read/Write RESTful HTTP API | HTTP API JSON over UDP | ADO.NET JDBC ODBC Proprietary native API | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | Ada C C# C++ D Delphi Eiffel Erlang Haskell Java JavaScript (Node.js) Objective-C OCaml Perl PHP Python Ruby Scheme Tcl | C# 3rd party library C++ Elixir 3rd party libraryGo 3rd party libraryJava 3rd party libraryJavaScript (Node.js) 3rd party libraryKotlin 3rd party libraryNim 3rd party libraryPerl 3rd party libraryPHP 3rd party libraryPython 3rd party libraryR 3rd party libraryRuby 3rd party libraryRust Scala 3rd party library | .NET Erlang Go community maintained clientJava JavaScript (Node.js) community maintained clientPerl community maintained clientPHP Python R Ruby community maintained clientScala community maintained client | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust Scala | Ada C C# C++ D Delphi Eiffel Erlang Haskell Java JavaScript (Node.js) Objective-C OCaml Perl PHP Python Ruby Scheme Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes | yes | user defined functions (Javascript) | no | yes proprietary syntax | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | horizontal partitioning | key based and custom | Sharding | Sharding in enterprise version only | horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Source-replica replication | Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages. | Configurable replication on table/partition-level | selectable replication factor in enterprise version only | Multi-source replication Source-replica replication | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Eventual Consistency Read-after-write consistency on record level | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | yes | no | no | no | yes not for MyISAM storage engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | no unique row identifiers can be used for implementing an optimistic concurrency control strategy | no | ACID not for MyISAM storage engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes table locks or row locks depending on storage engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | no | yes Depending on used storage engine | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | fine grained access rights according to SQL-standard | 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. | rights management via user accounts | simple rights management via user accounts | Users with fine-grained authorization concept no user groups or roles | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Amazon Aurora | ClickHouse | CrateDB | InfluxDB | MySQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | The enterprise database for time series, documents, and vectors. Distributed - Native... » more | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling... » more | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics... » more | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | Across all continents, CrateDB is used by companies of all sizes to meet the most... » more | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Market metrics | The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®... » more | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | See CrateDB pricing > » more | Open source core with closed source clustering available either on-premise or on... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | Sync Data from InfluxDB v2 to v3 With the Quix Template Infrastructure Monitoring Basics: Getting Started with Telegraf, InfluxDB, and Grafana Comparing Dates in Java: A Tutorial Python ARIMA Tutorial Time Series, InfluxDB, and Vector Databases | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We invite representatives of system vendors to contact us for updating and extending the system information, | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Related products and services | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 MySQL is the ideal solution for MySQL/MariaDB administration and development. » more Navicat Monitor is a safe, simple and agentless remote server monitoring tool for MySQL and many other database management systems. » more Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup. » more CData: Connect to Big Data & NoSQL through standard Drivers. » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We invite representatives of vendors of related products to contact us for presenting information about their offerings here. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Amazon Aurora | ClickHouse | CrateDB | InfluxDB | MySQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | Cloud-based DBMS's popularity grows at high rates The popularity of cloud-based DBMSs has increased tenfold in four years Amazon - the rising star in the DBMS market | Why Build a Time Series Data Platform? Time Series DBMS are the database category with the fastest increase in popularity Time Series DBMS as a new trend? | MySQL is the DBMS of the Year 2019 MariaDB strengthens its position in the open source RDBMS market The struggle for the hegemony in Oracle's database empire University of Nebraska-Omaha's ITD Lab migrates to Amazon Aurora with Babelfish, reducing database costs | Amazon ... Join the preview of Amazon Aurora Limitless Database | Amazon Web Services How RocketReach stabilized Amazon Aurora costs and improved performance with Amazon Aurora I/O-Optimized ... New – Amazon Aurora Optimized Reads for Aurora PostgreSQL with up to 8x query latency improvement for I/O ... Knowledge Bases for Amazon Bedrock now supports Amazon Aurora PostgreSQL and Cohere embedding models ... provided by Google News 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 TikTok Parent Open Sources Real-Time Data Warehouse Can LLMs Replace Data Analysts? Getting Answers Using SQL provided by Google News CrateDB Announces Availability of CrateDB on Google Cloud Marketplace CrateDB Appoints Sergey Gerasimenko as New CTO CrateDB Partners with HiveMQ to Deliver a Seamless Data Management Architecture for IoT How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things Real-Time Analytics Database Company CrateDB Names Lars Färnström as New CEO provided by Google News Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services dataFEED OPC Suite increases application security with OPC UA Tunnel and includes InfluxDB support | Electronics360 How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency AWS and InfluxData partner to offer managed time series database Timestream for InfluxDB Amazon Timestream: Managed InfluxDB for Time Series Data provided by Google News Amazon Aurora MySQL version 2 (with MySQL 5.7 compatibility) to version 3 (with MySQL 8.0 compatibility) upgrade ... General Availability: Azure MySQL Import feature for Azure Database for MySQL Single to Flexible Server migrations ... Zendesk Moves from DynamoDB to MySQL and S3 to Save over 80% in Costs First principles: Inside MySQL HeatWave Lakehouse on OCI Insert Data into a MySQL Database via a Python Script provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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