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

EdgeDB vs TiDB

OverviewComparisonAlternatives

Overview

TiDB
TiDB
Stacks76
Followers177
Votes28
GitHub Stars39.3K
Forks6.0K
EdgeDB
EdgeDB
Stacks17
Followers52
Votes0

EdgeDB vs TiDB: What are the differences?

Introduction:

Key Differences between EdgeDB and TiDB:

1. **Data Model**: EdgeDB uses a relational data model with support for objects, while TiDB follows a distributed NewSQL data model based on Google Spanner. This difference in data models impacts the way data is stored, queried, and manipulated in the database systems.
  
2. **Consistency Guarantees**: EdgeDB provides strong consistency guarantees, ensuring that data is always accurate and up-to-date, while TiDB offers eventual consistency, which may result in temporary inconsistencies in data across nodes in the database cluster.
  
3. **Scalability**: EdgeDB provides horizontal scalability through sharding, allowing for increased performance and storage capacity as the database grows. In contrast, TiDB offers horizontal scalability through its distributed architecture, enabling seamless expansion of the database across multiple nodes for high availability and data redundancy.
  
4. **Query Language**: EdgeDB uses a powerful and expressive query language called EdgeQL, designed for working with complex data structures and relationships. On the other hand, TiDB supports standard SQL queries for interacting with the database, making it easier for users familiar with SQL to work with the system.
  
5. **Consolidated Storage**: EdgeDB integrates storage and query processing in a single engine, optimizing performance and reducing latency for data retrieval. In contrast, TiDB separates storage and compute, allowing for flexible resource allocation and scalability based on workload demands.
  
6. **Transaction Support**: EdgeDB offers full ACID transactions with support for complex data integrity constraints and multi-statement transactions. TiDB also supports ACID transactions but requires additional configurations to ensure consistency across distributed transactions, making it more complex to manage transactional behavior.

In Summary, the key differences between EdgeDB and TiDB lie in their data models, consistency guarantees, scalability options, query languages, storage architectures, and transaction support.

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Detailed Comparison

TiDB
TiDB
EdgeDB
EdgeDB

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

An object-relational database that stores and describes the data as strongly typed objects and relationships between them.

Horizontal scalability;Asynchronous schema changes;Consistent distributed transactions;Compatible with MySQL protocol;Written in Go;NewSQL over TiKV;Multiple storage engine support
Strict, strongly typed schema; Powerful and clean query language; Ability to easily work with complex hierarchical data; Built-in support for schema migrations
Statistics
GitHub Stars
39.3K
GitHub Stars
-
GitHub Forks
6.0K
GitHub Forks
-
Stacks
76
Stacks
17
Followers
177
Followers
52
Votes
28
Votes
0
Pros & Cons
Pros
  • 9
    Open source
  • 7
    Horizontal scalability
  • 5
    Strong ACID
  • 3
    HTAP
  • 2
    Enterprise Support
No community feedback yet
Integrations
No integrations available
GraphQL
GraphQL
Python
Python

What are some alternatives to TiDB, EdgeDB?

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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