Douglas Butler presented on Massively parallel, lock free, distributed SQL database that is in-memory and on-disk with ACID transactions and support for JSON and geospatial data. The database has a 2 minute install and supports building real-time data pipelines in Python by extracting data from any source using a simple API and custom extractors.

2. Douglas Butler
Product Manager

4. massively parallel, lock free, FAST
distributed SQL database
in-memory, on-disk
ACID
JSON and geospatial
transactions and analytics

9. 2 Minute Install

11. A Simple Pipeline

12. from pystreamliner.api import Extractor
class CustomExtractor(Extractor):
def initialize(self, streaming_context,
sql_context, config, interval, logger):
logger.info("Initialized Extractor")
def next(self, streaming_context, time,
sql_context, config, interval, logger):
rdd = streaming_context._sc.parallelize([[x]
for x in range(10)])
return sql_context.createDataFrame(rdd,
["number"])

15. > memsql-ops pip install [package]
distributed cluster-wide
any Python package
bring your own

16. Real-time pipeline

17. Q & A time