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

Clickhouse vs TiDB

OverviewComparisonAlternatives

Overview

Clickhouse
Clickhouse
Stacks431
Followers543
Votes85
TiDB
TiDB
Stacks76
Followers177
Votes28
GitHub Stars39.3K
Forks6.0K

Clickhouse vs TiDB: What are the differences?

Introduction

Here we will discuss the key differences between ClickHouse and TiDB.

  1. Data Model: ClickHouse uses a columnar data model, which means that data is stored and processed column by column. On the other hand, TiDB uses a row-based data model, where data is stored and processed row by row. This difference in data model can impact the performance and efficiency of query processing.

  2. Distributed Architecture: ClickHouse is designed to be a distributed system by default, allowing for horizontal scaling and high availability. In contrast, TiDB is a distributed NewSQL database that combines the scalability of NoSQL with the ACID guarantees of SQL databases. Its distributed architecture enables automatic data sharding and efficient load balancing.

  3. Consistency Model: ClickHouse provides eventual consistency, which means that updates to the data might not be immediately visible to all the nodes in the cluster. TiDB, on the other hand, provides strong consistency, ensuring that updates are immediately visible and that concurrent transactions do not result in conflicts.

  4. SQL Compatibility: Although both ClickHouse and TiDB support SQL, they have differences in SQL compatibility. ClickHouse supports a subset of SQL, focusing on analytical workloads. TiDB, being a NewSQL database, aims to provide full SQL compatibility with features such as joins, indexes, and transactions.

  5. Replication Mechanism: ClickHouse uses a log-based replication mechanism, where log files are replicated between nodes. This approach allows for efficient replication and can handle high write throughput. TiDB, on the other hand, uses a Raft-based consensus protocol for replication, ensuring data consistency across nodes in the cluster.

  6. Storage Engine: ClickHouse uses its own storage engine optimized for columnar data processing, which provides high compression and fast query execution for analytical workloads. TiDB, on the other hand, uses a pluggable storage engine architecture and supports multiple engines like TiKV and TiFlash, providing flexibility for different use cases.

In summary, ClickHouse and TiDB differ in their data model, distributed architecture, consistency model, SQL compatibility, replication mechanism, and storage engine, making them suitable for different use cases and performance requirements.

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Detailed Comparison

Clickhouse
Clickhouse
TiDB
TiDB

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.

Inspired by the design of Google F1, TiDB supports the best features of both traditional RDBMS and NoSQL.

-
Horizontal scalability;Asynchronous schema changes;Consistent distributed transactions;Compatible with MySQL protocol;Written in Go;NewSQL over TiKV;Multiple storage engine support
Statistics
GitHub Stars
-
GitHub Stars
39.3K
GitHub Forks
-
GitHub Forks
6.0K
Stacks
431
Stacks
76
Followers
543
Followers
177
Votes
85
Votes
28
Pros & Cons
Pros
  • 21
    Fast, very very fast
  • 11
    Good compression ratio
  • 7
    Horizontally scalable
  • 6
    Utilizes all CPU resources
  • 5
    Open-source
Cons
  • 5
    Slow insert operations
Pros
  • 9
    Open source
  • 7
    Horizontal scalability
  • 5
    Strong ACID
  • 3
    HTAP
  • 2
    Enterprise Support

What are some alternatives to Clickhouse, TiDB?

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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