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Amazon Aurora

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Amazon RDS for Aurora vs TempoDB: What are the differences?

  1. Storage Engine: Amazon RDS for Aurora uses a modified version of the InnoDB storage engine, optimized for cloud-based environments, while TempoDB is a time-series database designed specifically for handling time-stamped data efficiently.
  2. Scaling: Amazon RDS for Aurora offers automatic scaling capabilities to accommodate growing workloads, whereas TempoDB's scaling options are more limited and may require manual intervention for large-scale operations.
  3. Data Model: Amazon RDS for Aurora supports relational database models, allowing for complex relationships between data, while TempoDB is optimized for storing and querying time-series data, such as sensor readings or log data.
  4. Query Performance: Amazon RDS for Aurora is designed to provide high-performance query processing for a wide range of use cases, whereas TempoDB excels in handling time-series data queries with optimized indexing and compression techniques.
  5. Backup and Recovery: Amazon RDS for Aurora offers automated backup and recovery options, including point-in-time recovery, while TempoDB may require custom backup solutions and manual recovery processes in case of data loss.
  6. Cost: Amazon RDS for Aurora follows a pay-as-you-go pricing model based on usage and storage, while TempoDB offers tiered pricing plans based on the volume of data stored and queried.

In Summary, the key differences between Amazon RDS for Aurora and TempoDB lie in their storage engines, scaling capabilities, data models, query performance, backup and recovery options, and pricing structures.

Decisions about Amazon Aurora and TempoDB
Phillip Manwaring
Developer at Coach Align · | 5 upvotes · 28.1K views

Using on-demand read/write capacity while we scale our userbase - means that we're well within the free-tier on AWS while we scale the business and evaluate traffic patterns.

Using single-table design, which is dead simple using Jeremy Daly's dynamodb-toolbox library

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Pros of Amazon Aurora
Pros of TempoDB
  • 14
    MySQL compatibility
  • 12
    Better performance
  • 10
    Easy read scalability
  • 9
    Speed
  • 7
    Low latency read replica
  • 2
    High IOPS cost
  • 1
    Good cost performance
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    Cons of Amazon Aurora
    Cons of TempoDB
    • 2
      Vendor locking
    • 1
      Rigid schema
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      What is Amazon Aurora?

      Amazon Aurora is a MySQL-compatible, relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora provides up to five times better performance than MySQL at a price point one tenth that of a commercial database while delivering similar performance and availability.

      What is TempoDB?

      TempoDB is the first database service for time series data (ex: measuring thermostat temperatures, network latencies, heart rates). Time series is a unique Big Data problem that breaks traditional databases (MySQL, MongoDB, etc). Today, businesses spend months and millions attempting to build solutions to manage all this data and yet still fail to store as much as they need or analyze it effectively. TempoDB is a purpose-built database service that enables businesses to store and analyze massive streams of time series data, so they can learn from the past, understand the present, and predict the future.

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      What companies use Amazon Aurora?
      What companies use TempoDB?
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      What are some alternatives to Amazon Aurora and TempoDB?
      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 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.
      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.
      Redis
      Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
      Amazon S3
      Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
      See all alternatives