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44 Ratings
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Score 8.3 out of 101
7 Ratings
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Score 8.9 out of 101

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Likelihood to Recommend

Amazon Aurora

Many places where Aurora is well suited:
  • If you are trying to build a serverless backend.
  • Amazon hosted relational database service (RDS). So we do not have to manage the database maintenance.
  • Backup and archival can be done to AWS S3, which is very convenient.
  • It provides high performance and scalability.
  • It's very secure. You could use AWS Key management service (KMS) to encrypt and store data on AWS Aurora.
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MemSQL

MemSQL is especially useful to serve as a back-end storage for spark streaming, and also small update problems. The streamliner technology is very helpful to process daily streaming data and consequent data analysis. Same SQL syntax is also very handy for people to learn and use.
Sachin Aggarwal profile photo

Pros

  • Amazon Aurora has high availability, since the customer started to use it, the database never had to be left out of service.
  • Amazon Aurora provides frequent and automated upgrades, which makes our database system always up to date on the latest features and security practices
  • Since Amazon Aurora uses MySQL as its core database, it is very easy to find specialized people to work. Amazon’s relational database management system also makes it very easy to expand and create new databases
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  • Faster query speed than traditional SQL database.
  • It con server in the pipeline to deal with streaming data with Kafka, spark streaming and MemSQL
  • It is very scalable.
Sachin Aggarwal profile photo

Cons

  • Cold-starts are part of the Aurora Serverless compromise, but they are painful nonetheless.
  • We're accustomed to sub-second metering for AWS Lambda; Aurora Serverless has 1-minute minimums for resources.
  • Aurora Serverless is compatible with MySQL 5.6. MySQL 5.6 lacks many of the features PostgreSQL users will expect.
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  • Provide faster python API for invoking MemSQL
  • MemSQL connection between spark failed when more than around 48 partitions data processing
  • Better tuning of MemSQL performance on Scale-up server
Sachin Aggarwal profile photo

Likelihood to Renew

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MemSQL5.0
Based on 1 answer
I still want to see the performance about using latest version of spark and memsql. About renewal, if there is a new and better version of spark-memsql connector, then maybe.
Tianwen Chu profile photo

Alternatives Considered

Aurora MySQL 5.6 lacks many of the features of PostgreSQL, and even more recent versions of MySQL or MariaDB. You may be able to tolerate these deficiencies; simple OLTP use-cases will be served adequately. Like RDS and DynamoDB, Aurora is managed and integrates well with other AWS products. Amazon Aurora Serverless can be much less expensive than RDS, however.
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I have tried using CSV as a back-end storage, yet I/O is very heavy, direct transit from spark to MemSQL in memory really beats.
Sachin Aggarwal profile photo

Return on Investment

  • Aurora Serverless has allowed us to inexpensively implement best-practices for our microservices architecture.
  • Aurora is mostly managed; our engineers can focus on features instead of database administration.
  • Aurora is capable of high throughput. Speed is not our first priority, but we still benefit from it.
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  • It offers me solution to solve spark storage problem
  • It adds more complexity of my application since multiple tech softwares are involved.
  • More types of bugs will be encountered when doing streamliner, including hardware connection.
Sachin Aggarwal profile photo

Pricing Details

Amazon Aurora

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

MemSQL

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details