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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Clickhouse vs Percona

Clickhouse vs Percona

OverviewComparisonAlternatives

Overview

Percona
Percona
Stacks143
Followers101
Votes0
Clickhouse
Clickhouse
Stacks431
Followers543
Votes85

Clickhouse vs Percona: What are the differences?

<Write Introduction here>
  1. Data Storage: ClickHouse is column-oriented, which means it stores data in columns, making it more efficient for analytical queries. On the other hand, Percona is row-oriented, storing data in rows, which is better suited for transactional workloads.

  2. Indexes: ClickHouse relies heavily on precomputed indexes, which significantly improve query performance by storing sorted data. Percona, on the other hand, uses traditional B-tree indexes, offering more flexibility but potentially slower performance for analytical queries.

  3. Scaling: ClickHouse is designed for horizontal scaling, allowing you to add more servers easily to handle increasing data volumes. Percona utilizes vertical scaling, where you need to upgrade hardware to increase performance, which can be more challenging and costly.

  4. Data Manipulation Language (DML): ClickHouse provides limited support for DML operations like update and delete, focusing more on analytical queries. Percona, being a SQL database, offers robust DML capabilities, making it more suitable for transactional workloads that require frequent updates and deletes.

  5. Data Types: ClickHouse has a limited set of supported data types optimized for analytical queries, whereas Percona supports a wide range of data types, making it more versatile for various types of workloads.

  6. Storage Engines: ClickHouse only supports its native storage engine, while Percona offers multiple storage engines, such as InnoDB and MyRocks, providing more options for optimizing performance based on specific use cases.

In Summary, ClickHouse and Percona differ in data storage, indexes, scaling, DML, data types, and storage engines, catering to different use cases based on their strengths and limitations.

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Detailed Comparison

Percona
Percona
Clickhouse
Clickhouse

It delivers enterprise-class software, support, consulting and managed services for both MySQL and MongoDB across traditional and cloud-based platforms.

It allows analysis of data that is updated in real time. It offers instant results in most cases: the data is processed faster than it takes to create a query.

Storing Key ring in a File; Encrypt InnoDB Data; Encrypt InnoDB Logs
-
Statistics
Stacks
143
Stacks
431
Followers
101
Followers
543
Votes
0
Votes
85
Pros & Cons
No community feedback yet
Pros
  • 21
    Fast, very very fast
  • 11
    Good compression ratio
  • 7
    Horizontally scalable
  • 6
    Utilizes all CPU resources
  • 5
    Great CLI
Cons
  • 5
    Slow insert operations
Integrations
MySQL
MySQL
SQLite
SQLite
MongoDB
MongoDB
No integrations available

What are some alternatives to Percona, Clickhouse?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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