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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Google Cloud Spanner vs Tokudb

Google Cloud Spanner vs Tokudb

OverviewComparisonAlternatives

Overview

Tokudb
Tokudb
Stacks3
Followers3
Votes0
GitHub Stars661
Forks129
Google Cloud Spanner
Google Cloud Spanner
Stacks57
Followers117
Votes3
GitHub Stars2.0K
Forks1.1K

Google Cloud Spanner vs Tokudb: What are the differences?

Google Cloud Spanner and Tokudb are both popular databases used for various applications. Here are the key differences between Google Cloud Spanner and Tokudb:

1. **Consistency Model**: Google Cloud Spanner uses a strong consistency model, ensuring that all reads return the latest committed data, while Tokudb follows a strict serializable isolation level, providing a higher level of consistency compared to Google Cloud Spanner.
2. **Horizontal Scalability**: Google Cloud Spanner offers horizontal scalability by distributing data across multiple nodes for better performance and fault tolerance, whereas Tokudb has limited horizontal scalability due to its design constraints.
3. **Data Distribution**: Google Cloud Spanner supports automatic sharding and distribution of data across nodes, enabling efficient data storage and retrieval, whereas Tokudb relies on manual partitioning methods for data distribution.
4. **Indexing Techniques**: Google Cloud Spanner utilizes a combination of primary key indexes and secondary indexes for efficient query processing and data retrieval, while Tokudb employs clustering indexes to optimize data storage and query performance.
5. **Replication Configuration**: Google Cloud Spanner provides configurable replication options with multi-region support for disaster recovery and high availability, whereas Tokudb offers limited replication configurations, primarily focusing on replication for fault tolerance within a single region.
6. **Data Compression**: Google Cloud Spanner incorporates advanced data compression techniques to reduce storage costs and optimize performance, whereas Tokudb may not offer the same level of data compression capabilities.

In Summary, Google Cloud Spanner and Tokudb differ in terms of consistency models, horizontal scalability, data distribution, indexing techniques, replication configurations, and data compression capabilities.

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Detailed Comparison

Tokudb
Tokudb
Google Cloud Spanner
Google Cloud Spanner

It is an open-source, high-performance storage engine for MySQL and MariaDB. It achieves this by using a fractal tree index. It is scalable, ACID and MVCC compliant, provides indexing-based query improvements, offers online schema modifications, and reduces slave lag for both hard disk drives and flash memory.

It is a globally distributed database service that gives developers a production-ready storage solution. It provides key features such as global transactions, strongly consistent reads, and automatic multi-site replication and failover.

Fast and scalable service; Better performance; Stronger ROI; Higher availability
Global transactions; Strongly consistent reads; Automatic multi-site replication; Failover.
Statistics
GitHub Stars
661
GitHub Stars
2.0K
GitHub Forks
129
GitHub Forks
1.1K
Stacks
3
Stacks
57
Followers
3
Followers
117
Votes
0
Votes
3
Pros & Cons
No community feedback yet
Pros
  • 1
    Scalable
  • 1
    Horizontal scaling
  • 1
    Strongly consistent
Integrations
MySQL
MySQL
MariaDB
MariaDB
MySQL
MySQL
PostgreSQL
PostgreSQL
MongoDB
MongoDB
SQLite
SQLite

What are some alternatives to Tokudb, Google Cloud Spanner?

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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