DBMS > Amazon Aurora vs. ClickHouse vs. CrateDB vs. Datastax Enterprise vs. Elasticsearch
System Properties Comparison Amazon Aurora vs. ClickHouse vs. CrateDB vs. Datastax Enterprise vs. Elasticsearch
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Name | Amazon Aurora Xexclude from comparison | ClickHouse Xexclude from comparison | CrateDB Xexclude from comparison | Datastax Enterprise Xexclude from comparison | Elasticsearch 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 | DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform. | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Relational DBMS | Document store Spatial DBMS Search engine Time Series DBMS Vector DBMS | Wide column store | Search engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store | Time Series DBMS | Relational DBMS | Document store Graph DBMS Spatial DBMS Search engine Vector DBMS | Document store Spatial DBMS Vector DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/rds/aurora | clickhouse.com | cratedb.com | www.datastax.com/products/datastax-enterprise | www.elastic.co/elasticsearch | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html | clickhouse.com/docs | cratedb.com/docs | docs.datastax.com | www.elastic.co/guide/en/elasticsearch/reference/current/index.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Amazon | Clickhouse Inc. | Crate | DataStax | Elastic | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2015 | 2016 | 2013 | 2011 | 2010 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | v24.4.1.2088-stable, May 2024 | 6.8, April 2020 | 8.6, January 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | Open Source Apache 2.0 | Open Source | commercial | Open Source Elastic License | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 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. | Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C++ | Java | Java | Java | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | FreeBSD Linux macOS | All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support | Linux OS X | All OS with a Java VM | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | yes | Flexible Schema (defined schema, partial schema, schema free) | schema-free | schema-free Flexible type definitions. Once a type is defined, it is persistent | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | yes | 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 | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | yes All search fields are automatically indexed | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes | Close to ANSI SQL (SQL/JSON + extensions) | yes, but no triggers and constraints, and PostgreSQL compatibility | SQL-like DML and DDL statements (CQL); Spark SQL | SQL-like query language | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | Proprietary protocol CQL (Cassandra Query Language) TinkerPop Gremlin with DSE Graph | Java API RESTful HTTP/JSON 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 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 Erlang Go community maintained client Java JavaScript (Node.js) community maintained client Perl community maintained client PHP Python R Ruby community maintained client Scala community maintained client | C C# C++ Java JavaScript (Node.js) PHP Python Ruby | .Net Groovy Community Contributed Clients Java JavaScript Perl PHP Python Ruby | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | yes | user defined functions (Javascript) | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | no | no | yes | yes by using the 'percolation' feature | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | horizontal partitioning | key based and custom | Sharding | Sharding no "single point of failure" | Sharding | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | configurable replication factor, datacenter aware, advanced replication for edge computing | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | no | yes | ES-Hadoop Connector | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 Tunable Consistency consistency level can be individually decided with each write operation | Eventual Consistency Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 Atomicity and isolation are supported for single operations | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | Memcached and Redis integration | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | Access rights for users can be defined per object | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon Aurora | ClickHouse | CrateDB | Datastax Enterprise | Elasticsearch | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | The enterprise database for time series, documents, and vectors. Distributed - Native... » more | DataStax Enterprise is scale-out data infrastructure for enterprises that need to... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling... » more | Supporting the following application requirements: Zero downtime - Built on Apache... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics... » more | Applications that must be massively and linearly scalable with 100% uptime and able... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Across all continents, CrateDB is used by companies of all sizes to meet the most... » more | Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®... » more | Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | See CrateDB pricing > » more | Annual subscription » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Amazon Aurora | ClickHouse | CrateDB | Datastax Enterprise | Elasticsearch | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | 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 Join the preview of Amazon Aurora Limitless Database | Amazon Web Services Handle tables without primary keys while creating Amazon Aurora PostgreSQL zero-ETL integrations with Amazon ... 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 ... Build generative AI applications with Amazon Aurora and Knowledge Bases for Amazon Bedrock | Amazon Web Services 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 From Open Source to SaaS: the Journey of ClickHouse Snowflake vs. BigQuery vs. ClickHouse: Mastering Cost-Effective Business Analytics provided by Google News CrateDB Partners with HiveMQ to Deliver a Seamless Data Management Architecture for IoT CrateDB Announces Availability of CrateDB on Google Cloud Marketplace CrateDB Appoints Sergey Gerasimenko as New CTO 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 DataStax and LlamaIndex Partner to Make Building RAG Applications Easier than Ever for GenAI Developers DataStax Introduces Enhanced RAG Capabilities Through Astra DB and NVIDIA Tech DataStax Rolls Out Vector Search for Astra DB to Support Gen AI DataStax adds vector search to boost support for generative AI workloads DataStax goes vector searching with Astra DB – Blocks and Files provided by Google News Red Hat and Elastic Fuel Retrieval Augmented Generation for GenAI Use Cases Netflix Uses Elasticsearch Percolate Queries to Implement Reverse Searches Efficiently Splunk vs Elasticsearch | A Comparison and How to Choose ElasticSearch Goes Deep on OpenTelemetry with eBPF Donation Introducing Elasticsearch Vector Database to Azure OpenAI Service On Your Data (Preview) provided by Google News |
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