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1. DATABASES AND
QUERIES
MATCHING PERFORMANCE AND RELIABILITY

2. Dave Smith
VP, Engineering
@dizzyd

3. SURVEY
• Who has hit problems scaling RDBMS?
• Who is using non-relational databases?

4. QUERIES
• Relational
• Key/value (document)
• Text retrieval (full-text search)
• Graph
• Time-series
• Geospatial

5. QUERIES(CONT. )
• What questions are you asking of your data?
• Get a record by a key
• Find records based on a relationship
• Find all documents with a given term
• Apply operation to metrics within a timeframe

6. It is possible to rewrite most queries in other
forms.

7. PERFORMANCE
• Access patterns
• Read/write mix
• Sequential vs. Pareto vs. uniformly random
• Throughput - how many requests/sec?
• Latency - how long does it take to service a single request?
• Always a distribution! Mean is meaningless…
• Data size
• Total size of dataset
• Size per item in dataset

8. RELIABILITY
• How can databases fail?
• Disks -> integrity checking
• Nodes -> replication
• Network -> versioning
• Software -> (all of above)
• Overload -> elasticity
• Key questions
• How well does the system tolerate failure?
• How well does the system deal with unexpected load?

9. It can be impossible to distinguish between a slow
node and a failed node.

10. UGLY TRUTHS
• All databases require tuning
• Failure is hard to test — most people don’t bother
• Networks fail — especially under high load
• The more your database does, the more ways it can
fail
• More code == more bugs

11. CHOICES, CHOICES…
• MySQL, Postgres, Oracle
• CouchDB, MongoDB, RethinkDB
• Riak, Cassandra
• HBase, Hypertable
• MemSQL, CouchBase
• ElasticSearch, SOLR
• Neo4J, Titan