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Building a Startup
 with NoSQL

Building a Startup
 with NoSQL

These slides are from a talk I gave at NoSQL Matters 2014 in Barcelona. It's not very technical per-se and more focussed on what kind of decision making is important to choose NoSQL technology (especially) when you are a startup.

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Sebastian Cohnen

December 01, 2014
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Transcript

  1. Building a Startup
 with NoSQL Sebastian Cohnen, @tisba
 stormforger.com, @StormForgerApp


    NoSQL Matters Barcelona 2014
  2. About me • Sebastian Cohnen, M. Sc. • Developer &

    Founder from Cologne, Germany • (Web-) Architectures, Performance & Scalability • Founder of StormForger.com
 (services around load testing HTTP-based systems)
  3. Startups • agile & open minded • small teams, pragmatic

    • solve new problems
  4. NoSQL? "A NoSQL (often interpreted as Not Only SQL) database

    provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases." https://en.wikipedia.org/wiki/NoSQL "Motivations for this approach include simplicity of design, horizontal scaling and finer control over availability."
  5. NoSQL • Ease of use (development & operations) • Very

    special problem
  6. StormForger

  7. StormForger • load and performance testing of HTTP APIs •

    SaaS product • plan, configure and execute tests • analyze and compare results
  8. We are a startup!

  9. Our Needs • handle highly structured, complex data • ingest,

    process and query time series data • caching of structured data • centralized logging and log analysis
  10. How to find the
 perfect solution?

  11. There isn't one :-/

  12. Polyglot Persistence (NoSQL)
 Technology Problem

  13. …but be careful • What are the downsides and tradeoffs?

    • Availability of tooling? • How mature is the technology? • What about (community or commercial) support?
  14. Back to StormForger's needs…

  15. • SQL-ish, declarative query language • easy to get started

    with • powerful background/stream processing Time Series Data
  16. Caching • very, very fast • primitive functions to work

    with data structures • awesome community
  17. • ELK (Elastic Search + Logstash + Kibana) • Centralized,

    aggregated logging • Great analysis and search features Logging
  18. Structured Data • Not really tackled yet • For now:

    serialize and store as TEXT in RDMS
  19. Structured Data (2) • we already evaluated some solutions •

    great query language (AQL) • support for JOINS & Graphs
  20. Conclusion • focus on ease of use aspects • be

    pragmatic and think agile • pick the right tool for the job
  21. And if you think you found the right solution… …there

    are always alternatives…
  22. What about using a SQL DB for NoSQL?

  23. PostgreSQL • hstore: Key/Value • json & jsonb: JSON data

    • just use your existing tools • query via SQL, indexable, …
  24. None
  25. Thanks! https://stormforger.com Sebastian Cohnen (@tisba) Questions?