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

TiDB vs Vertica

OverviewComparisonAlternatives

Overview

Vertica
Vertica
Stacks90
Followers120
Votes16
TiDB
TiDB
Stacks76
Followers177
Votes28
GitHub Stars39.3K
Forks6.0K

TiDB vs Vertica: What are the differences?

Introduction:

Key Differences Between TiDB and Vertica:

1. **Architecture**: TiDB is a distributed NewSQL database that combines the horizontal scalability of distributed systems with the ACID compliance of traditional RDBMS, whereas Vertica is a columnar database designed for analytical workloads, offering high-performance analytics and SQL queries on large datasets.
   
2. **Consistency Model**: TiDB uses optimistic concurrency control for transactions, ensuring strong consistency across distributed clusters, while Vertica focuses on high-speed analytics and supports eventual consistency for faster query processing.
   
3. **Data Partitioning**: TiDB automatically partitions data across multiple nodes using its placement driver, allowing for seamless scalability and load balancing, whereas Vertica relies on projections to manage data distribution and optimize query performance.
   
4. **Storage Engine**: TiDB uses TiKV as its distributed Key-Value storage engine, ensuring fault tolerance and high availability, while Vertica utilizes its optimized storage formats and compression techniques for efficient data storage and retrieval.
   
5. **Data Processing**: TiDB supports both OLTP and OLAP workloads by combining its distributed processing capabilities with analytical features, whereas Vertica is primarily focused on OLAP workloads and provides advanced analytics functionalities for data warehousing applications.
   
6. **Community Support**: TiDB has a growing open-source community and ecosystem, with contributors from around the world, while Vertica is backed by a commercial vendor, Micro Focus, offering enterprise-focused support and services.

In Summary, TiDB offers a distributed NewSQL architecture with strong consistency and seamless scalability, while Vertica specializes in high-performance analytics with columnar storage and advanced query optimization techniques.

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Detailed Comparison

Vertica
Vertica
TiDB
TiDB

It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.

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

Analyze All of Your Data. No longer move data or settle for siloed views;Achieve Scale and Performance;Fear of growing data volumes and users is a thing of the past;Future-Proof Your Analytics
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
90
Stacks
76
Followers
120
Followers
177
Votes
16
Votes
28
Pros & Cons
Pros
  • 3
    Shared nothing or shared everything architecture
  • 1
    End-to-End ML Workflow Support
  • 1
    Pre-Aggregation for Cubes (LAPS)
  • 1
    Freedom from Underlying Storage
  • 1
    All You Need for IoT, Clickstream or Geospatial
Pros
  • 9
    Open source
  • 7
    Horizontal scalability
  • 5
    Strong ACID
  • 3
    HTAP
  • 2
    Mysql Compatibility
Integrations
Oracle
Oracle
Golang
Golang
MongoDB
MongoDB
MySQL
MySQL
Sass
Sass
Mode
Mode
PowerBI
PowerBI
Tableau
Tableau
Talend
Talend
No integrations available

What are some alternatives to Vertica, 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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