StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Google Cloud Spanner vs TokuMX

Google Cloud Spanner vs TokuMX

OverviewComparisonAlternatives

Overview

TokuMX
TokuMX
Stacks6
Followers16
Votes3
GitHub Stars705
Forks97
Google Cloud Spanner
Google Cloud Spanner
Stacks57
Followers117
Votes3
GitHub Stars2.0K
Forks1.1K

Google Cloud Spanner vs TokuMX: What are the differences?

## Introduction
Google Cloud Spanner and TokuMX are both popular databases, but they have key differences that set them apart.

## 1. Scalability:
Google Cloud Spanner is fully managed and offers global scalability with strong consistency guarantees, making it suitable for large-scale and global applications. In contrast, TokuMX is a distributed database system that is designed for high performance but may not offer the same level of scalability as Spanner.

## 2. Data Model:
Google Cloud Spanner supports SQL queries and ACID transactions, making it easier for developers to work with. On the other hand, TokuMX is a document-oriented database that uses JSON-like documents for storing data, which may be more suitable for applications that require flexibility in data schema.

## 3. Secondary Indexes:
Google Cloud Spanner supports secondary indexes, which allows for efficient querying of data. TokuMX also supports secondary indexes but is optimized for high write throughput, which may impact query performance in certain scenarios.

## 4. Consistency Model:
Google Cloud Spanner uses a distributed, horizontally scalable architecture with a global, strong consistency model. TokuMX uses a single-master replication model with eventual consistency, which may be sufficient for some applications but may not offer the same level of consistency as Spanner.

## 5. Automated Maintenance:
Google Cloud Spanner provides automated backups, monitoring, and maintenance, reducing the operational burden on developers. TokuMX also has some automated maintenance features but may require more manual tuning and monitoring in comparison to Spanner.

## 6. Pricing:
Google Cloud Spanner follows a pay-as-you-go pricing model based on usage, while TokuMX is available under a community edition license with the option to upgrade to a paid version for additional features and support.

In Summary, Google Cloud Spanner and TokuMX differ in terms of scalability, data model, secondary indexes, consistency model, automated maintenance, and pricing models.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Detailed Comparison

TokuMX
TokuMX
Google Cloud Spanner
Google Cloud Spanner

TokuMX is a drop-in replacement for MongoDB, and offers 20X performance improvements, 90% reduction in database size, and support for ACID transactions with MVCC. TokuMX has the same binaries, supports the same drivers, data model, and features of MongoDB, because it shares much of its code with MongoDB.

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.

-
Global transactions; Strongly consistent reads; Automatic multi-site replication; Failover.
Statistics
GitHub Stars
705
GitHub Stars
2.0K
GitHub Forks
97
GitHub Forks
1.1K
Stacks
6
Stacks
57
Followers
16
Followers
117
Votes
3
Votes
3
Pros & Cons
Pros
  • 3
    When your two-week MongoDB love affair ends, try this
Pros
  • 1
    Scalable
  • 1
    Horizontal scaling
  • 1
    Strongly consistent
Integrations
MongoDB
MongoDB
MySQL
MySQL
PostgreSQL
PostgreSQL
MongoDB
MongoDB
SQLite
SQLite

What are some alternatives to TokuMX, 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.

Related Comparisons

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot

Liquibase
Flyway

Flyway vs Liquibase