MemSQL Reviews

7 Ratings
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Score 9.1 out of 101

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Reviews (1-2 of 2)

Sachin Aggarwal profile photo
Score 10 out of 10
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Verified User
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One of our primary factors was performance - need real-time (sub-second) query response over 100 billion rows or more. helped us use the product appropriately, best practices, great support each time we reached out. administration/maintenance work tasks could be better - we built our own scripts/tooling to address this.
  • 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.
  • 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
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.
Read Sachin Aggarwal's full review
Tianwen Chu profile photo
August 02, 2016

MemSQL backup Spark

Score 7 out of 10
Vetted Review
Verified User
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MemSQL is used as a persistent storage solution for Spark. We use memsql-spark connector (Scala code) to bridge two techs. I am leading projects of using spark and memsql to process life science data. It solved the spark storage issue.
  • 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.
  • Better tuning of MemSQL performance on Scale-up server
  • MemSQL connection between spark failed when more than around 48 partitions data processing
  • Provide faster python API for invoking MemSQL
If data has too many joins necessities, then think of using graphdatabase technology rather than relational table.
Read Tianwen Chu's full review

About MemSQL

MemSQL is a NoSQL database offering from the company of the same name in San Francisco.

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