DBMS > ClickHouse vs. Ignite vs. Kinetica vs. Oracle Berkeley DB vs. Redis
System Properties Comparison ClickHouse vs. Ignite vs. Kinetica vs. Oracle Berkeley DB vs. Redis
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Name | ClickHouse Xexclude from comparison | Ignite Xexclude from comparison | Kinetica Xexclude from comparison | Oracle Berkeley DB Xexclude from comparison | Redis 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. | Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale. | Fully vectorized database across both GPUs and CPUs | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Key-value store Relational DBMS | Relational DBMS | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Time Series DBMS | Spatial DBMS Time Series 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 | ignite.apache.org | www.kinetica.com | www.oracle.com/database/technologies/related/berkeleydb.html | redis.com redis.io | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | clickhouse.com/docs | apacheignite.readme.io/docs | docs.kinetica.com | docs.oracle.com/cd/E17076_05/html/index.html | docs.redis.com/latest/index.html redis.io/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Clickhouse Inc. | Apache Software Foundation | Kinetica | Oracle originally developed by Sleepycat, which was acquired by Oracle | Redis project core team, inspired by Salvatore Sanfilippo Development sponsored by Redis Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2016 | 2015 | 2012 | 1994 | 2009 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | v24.4.1.2088-stable, May 2024 | Apache Ignite 2.6 | 7.1, August 2021 | 18.1.40, May 2020 | 7.2.5, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache 2.0 | Open Source Apache 2.0 | commercial | Open Source commercial license available | Open Source source-available extensions (modules), commercial licenses for Redis Enterprise | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C++ | C++, Java, .Net | C, C++ | C, Java, C++ (depending on the Berkeley DB edition) | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | FreeBSD Linux macOS | Linux OS X Solaris Windows | Linux | 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 | yes | yes | schema-free | schema-free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | no | partial Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | yes | no | yes only with the Berkeley DB XML edition | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | yes with RediSearch module | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | Close to ANSI SQL (SQL/JSON + extensions) | ANSI-99 for query and DML statements, subset of DDL | SQL-like DML and DDL statements | yes SQL interfaced based on SQLite is available | with RediSQL module | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | gRPC HTTP REST JDBC MySQL wire protocol ODBC PostgreSQL wire protocol Proprietary protocol | HDFS API Hibernate JCache JDBC ODBC Proprietary protocol RESTful HTTP API Spring Data | JDBC ODBC RESTful HTTP API | proprietary protocol RESP - REdis Serialization Protocol | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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++ Java PHP Python Ruby Scala | C++ Java JavaScript (Node.js) Python | .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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | yes (compute grid and cache interceptors can be used instead) | user defined functions | no | Lua; Redis Functions coming in Redis 7 (slides and Github) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes (cache interceptors and events) | yes triggers when inserted values for one or more columns fall within a specified range | yes only for the SQL API | publish/subscribe channels provide some trigger functionality; RedisGears | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | key based and custom | Sharding | Sharding | none | Sharding Automatic hash-based sharding with support for hash-tags for manual sharding | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages. | yes (replicated cache) | Source-replica replication | Source-replica replication | Multi-source replication with Redis Enterprise Pack Source-replica replication Chained replication is supported | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | yes (compute grid and hadoop accelerator) | no | no | through RedisGears | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Immediate Consistency or Eventual Consistency depending on configuration | 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 | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID | no | ACID | Atomic execution of command blocks and scripts and optimistic locking | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes Data access is serialized by the server | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes Configurable mechanisms for persistency via snapshots and/or operations logs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | yes GPU vRAM or System RAM | 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. | Security Hooks for custom implementations | Access rights for users and roles on table level | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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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 | Redisson PRO: The ultra-fast Redis Java Client. » more Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs. » more Navicat for Redis: the award-winning Redis management tool with an intuitive and powerful graphical interface. » more CData: Connect to Big Data & NoSQL through standard Drivers. » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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ClickHouse | Ignite | Kinetica | Oracle Berkeley DB | Redis | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 Why Clickhouse Should Be Your Next Database ClickHouse Cloud & Amazon S3 Express One Zone: Making a blazing fast analytical database even faster | Amazon ... Intel Xeon 6766E/6780E Sierra Forest vs. Ampere Altra Performance & Power Efficiency Review A 1000x Faster Database Solution: ClickHouse’s Aaron Katz From Open Source to SaaS: the Journey of ClickHouse provided by Google News GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024 GridGain Showcases Power of Apache Ignite at Community Over Code Conference Apache Ignite: An Overview GridGain Unified Real-Time Data Platform Version 8.9 Addresses Today's More Complex Real-Time Data Processing ... What is Apache Ignite? How is Apache Ignite Used? provided by Google News Kinetica Delivers Real-Time Vector Similarity Search Kinetica Elevates RAG with Fast Access to Real-Time Data Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise Transforming spatiotemporal data analysis with GPUs and generative AI provided by Google News ACM recognizes far-reaching technical achievements with special awards Margo Seltzer Named ACM Athena Lecturer for Technical and Mentoring Contributions Oracle buys Sleepycat Software Margo I. Seltzer | Berkman Klein Center How to store financial market data for backtesting provided by Google News Redis moves to source-available licenses Redis switches licenses, acquires Speedb to go beyond its core in-memory database Redis expands data management capabilities with Speedb acquisition – Blocks and Files In-memory database Redis wants to dabble in disk Redis acquires storage engine startup Speedb to enhance its open-source database provided by Google News |
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