DBMS > ClickHouse vs. Datastax Enterprise vs. Oracle Berkeley DB vs. Redis vs. TerarkDB
System Properties Comparison ClickHouse vs. Datastax Enterprise vs. Oracle Berkeley DB vs. Redis vs. TerarkDB
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Name | ClickHouse Xexclude from comparison | Datastax Enterprise Xexclude from comparison | Oracle Berkeley DB Xexclude from comparison | Redis Xexclude from comparison | TerarkDB 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. | 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. | Widely used in-process key-value store | Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies. | A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Wide column store | Key-value store supports sorted and unsorted key sets Native XML DBMS in the Oracle Berkeley DB XML version | Key-value store Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence | Key-value store | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Time Series DBMS | Document store Graph DBMS Spatial DBMS Search engine Vector DBMS | Document store with RedisJSON Graph DBMS with RedisGraph Spatial DBMS Search engine with RediSearch Time Series DBMS with RedisTimeSeries Vector DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | clickhouse.com | www.datastax.com/products/datastax-enterprise | www.oracle.com/database/technologies/related/berkeleydb.html | redis.com redis.io | github.com/bytedance/terarkdb | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | clickhouse.com/docs | docs.datastax.com | docs.oracle.com/cd/E17076_05/html/index.html | docs.redis.com/latest/index.html redis.io/docs | bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Clickhouse Inc. | DataStax | Oracle originally developed by Sleepycat, which was acquired by Oracle | Redis project core team, inspired by Salvatore Sanfilippo Development sponsored by Redis Inc. | ByteDance, originally Terark | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2016 | 2011 | 1994 | 2009 | 2016 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | v24.4.1.2088-stable, May 2024 | 6.8, April 2020 | 18.1.40, May 2020 | 7.2.4, January 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache 2.0 | commercial | Open Source commercial license available | Open Source source-available extensions (modules), commercial licenses for Redis Enterprise | commercial restricted open source version available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 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. | Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C++ | Java | C, Java, C++ (depending on the Berkeley DB edition) | C | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | FreeBSD Linux macOS | Linux OS X | AIX Android FreeBSD iOS Linux OS X Solaris VxWorks Windows | BSD Linux OS X Windows ported and maintained by Microsoft Open Technologies, Inc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | schema-free | schema-free | schema-free | schema-free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | no | partial Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 only with the Berkeley DB XML edition | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes with RediSearch module | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | Close to ANSI SQL (SQL/JSON + extensions) | SQL-like DML and DDL statements (CQL); Spark SQL | yes SQL interfaced based on SQLite is available | with RediSQL module | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | gRPC HTTP REST JDBC MySQL wire protocol ODBC PostgreSQL wire protocol Proprietary protocol | Proprietary protocol CQL (Cassandra Query Language) TinkerPop Gremlin with DSE Graph | proprietary protocol RESP - REdis Serialization Protocol | C++ API Java API | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | C C# C++ Java JavaScript (Node.js) PHP Python Ruby | .Net Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET others Third-party libraries to manipulate Berkeley DB files are available for many languages C C# C++ Java JavaScript (Node.js) 3rd party binding Perl Python Tcl | C C# C++ Clojure Crystal D Dart Elixir Erlang Fancy Go Haskell Haxe Java JavaScript (Node.js) Lisp Lua MatLab Objective-C OCaml Pascal Perl PHP Prolog Pure Data Python R Rebol Ruby Rust Scala Scheme Smalltalk Swift Tcl Visual Basic | C++ Java | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | no | no | Lua; Redis Functions coming in Redis 7 (slides and Github) | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes | yes only for the SQL API | publish/subscribe channels provide some trigger functionality; RedisGears | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | key based and custom | Sharding no "single point of failure" | none | Sharding Automatic hash-based sharding with support for hash-tags for manual sharding | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages. | configurable replication factor, datacenter aware, advanced replication for edge computing | Source-replica replication | Multi-source replication with Redis Enterprise Pack Source-replica replication Chained replication is supported | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | yes | no | through RedisGears | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency Tunable Consistency consistency level can be individually decided with each write operation | Eventual Consistency Causal consistency can be enabled in Active-Active databases Strong consistency with Redis Raft Strong eventual consistency with Active-Active | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | no Atomicity and isolation are supported for single operations | ACID | Atomic execution of command blocks and scripts and optimistic locking | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes Data access is serialized by the server | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes Configurable mechanisms for persistency via snapshots and/or operations logs | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | yes | yes | 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. | Access rights for users can be defined per object | no | Access Control Lists (ACLs): redis.io/docs/management/security/acl LDAP and Role-Based Access Control (RBAC) for Redis Enterprise Mutual TLS authentication: redis.io/docs/management/security/encryption Password-based authentication | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
ClickHouse | Datastax Enterprise | Oracle Berkeley DB | Redis | TerarkDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | DataStax Enterprise is scale-out data infrastructure for enterprises that need to... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Supporting the following application requirements: Zero downtime - Built on Apache... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Applications that must be massively and linearly scalable with 100% uptime and able... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Annual subscription » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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3rd parties | DoubleCloud: 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 | Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.
» more CData: Connect to Big Data & NoSQL through standard Drivers. » more Redisson PRO: The ultra-fast Redis Java Client. » more Navicat for Redis: the award-winning Redis management tool with an intuitive and powerful graphical interface. » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
ClickHouse | Datastax Enterprise | Oracle Berkeley DB | Redis | TerarkDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | PostgreSQL is the DBMS of the Year 2018 MySQL, PostgreSQL and Redis are the winners of the March ranking MongoDB is the DBMS of the year, defending the title from last year | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the 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 | 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 | Margo Seltzer Named ACM Athena Lecturer for Technical and Mentoring Contributions ACM recognizes far-reaching technical achievements with special awards Database Trends Report: SQL Beats NoSQL, MySQL Most Popular -- ADTmag A Quick Look at Open Source Databases for Mobile App Development Motorola A780 Linux based smartphone to have mobile database provided by Google News | Linux Foundation marshals support for open source alternative to Redis Redis switches licenses, acquires Speedb to go beyond its core in-memory database Redis acquires storage engine startup Speedb to enhance its open-source database Redis moves to source-available licenses Valkey: A Redis Fork With a Future provided by Google News |
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