Google Cloud Datastore vs MySQL Performance Analyzer

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Google Cloud Datastore

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MySQL Performance Analyzer

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Google Cloud Datastore vs MySQL Performance Analyzer: What are the differences?

Developers describe Google Cloud Datastore as "A Fully Managed NoSQL Data Storage Service". Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries. On the other hand, MySQL Performance Analyzer is detailed as "MySQL Performance Analyzer by Yahoo". MySQL Performance Analyzer is an open source project for MySQL performance monitoring and analysis.

Google Cloud Datastore can be classified as a tool in the "NoSQL Database as a Service" category, while MySQL Performance Analyzer is grouped under "Database Tools".

MySQL Performance Analyzer is an open source tool with 1.36K GitHub stars and 194 GitHub forks. Here's a link to MySQL Performance Analyzer's open source repository on GitHub.

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Pros of Google Cloud Datastore
Pros of MySQL Performance Analyzer
  • 7
    High scalability
  • 2
    Serverless
  • 2
    Ability to query any property
  • 1
    Pay for what you use
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    - No public GitHub repository available -

    What is Google Cloud Datastore?

    Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries.

    What is MySQL Performance Analyzer?

    MySQL Performance Analyzer is an open source project for MySQL performance monitoring and analysis.

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    What companies use Google Cloud Datastore?
    What companies use MySQL Performance Analyzer?
    See which teams inside your own company are using Google Cloud Datastore or MySQL Performance Analyzer.
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    What tools integrate with Google Cloud Datastore?
    What tools integrate with MySQL Performance Analyzer?
    What are some alternatives to Google Cloud Datastore and MySQL Performance Analyzer?
    Amazon DynamoDB
    With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
    Redis
    Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
    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.
    Elasticsearch
    Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
    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.
    See all alternatives