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.

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, …
25. Thanks! https://stormforger.com Sebastian Cohnen (@tisba) Questions?