Couchbase vs Vitess: What are the differences?
Couchbase: Document-Oriented NoSQL Database. Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands; Vitess: It is a database clustering system for horizontal scaling of MySQL. It is a database solution for deploying, scaling and managing large clusters of MySQL instances. It’s architected to run as effectively in a public or private cloud architecture as it does on dedicated hardware. It combines and extends many important MySQL features with the scalability of a NoSQL database.
Couchbase and Vitess can be categorized as "Databases" tools.
Some of the features offered by Couchbase are:
- JSON document database
- N1QL (SQL-like query language)
- Secondary Indexing
On the other hand, Vitess provides the following key features:
- Connection pooling
What is Couchbase?
What is Vitess?
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They're critical to the business data and operated by an ecosystem of tools. But once the tools have been used, it was important to verify that the data remains as expected at all times. Even with the best efforts to prevent errors, inconsistencies are bound to creep at any stage. In order to test the code in a comprehensive manner, Slack developed a structure known as a consistency check framework.
This is a responsive and personalized framework that can meaningfully analyze and report on your data with a number of proactive and reactive benefits. This framework is important because it can help with repair and recovery from an outage or bug, it can help ensure effective data migration through scripts that test the code post-migration, and find bugs throughout the database. This framework helped prevent duplication and identifies the canonical code in each case, running as reusable code.
The framework was created by creating generic versions of the scanning and reporting code and an interface for the checking code. The checks could be run from the command line and either a single team could be scanned or the whole system. The process was improved over time to further customize the checks and make them more specific. In order to make this framework accessible to everyone, a GUI was added and connected to the internal administrative system. The framework was also modified to include code that can fix certain problems, while others are left for manual intervention. For Slack, such a tool proved extremely beneficial in ensuring data integrity both internally and externally.
We use Couchbase heavily in our PowerStandings platform to enable real-time analytics of agent data, as well as data storage for parts of our new Playbooks product.
Main data storage. Any writes to Couchbase auto-replicate to Elasticsearch (via XDRC) and from there on propagate into the internal Jezebel pipeline via opes.