Josh Innis
Senior Postgres Query Tuner Expert at ServiceNow
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolJosh Innis is a senior database-focused software engineer with 11 years of experience building high-performance data systems and extensions for PostgreSQL and SQL Server. He has engineered novel in-database solutions—like a sub-plan caching engine and an unrestricted Python runtime for Postgres—and led performance benchmarking and automated regression testing for vector search features. A core contributor to Apache AGE, Josh implemented storage, query execution (including MERGE and DELETE), and agtype improvements that helped make graph analytics fast and indexable inside Postgres. His background spans deep low-level profiling (XPerf, Kernrate) to pragmatic schema and ETL redesigns that produced dramatic speedups in production reporting. Based in the Bay Area and a UCSC CS graduate, he blends systems-level optimization with product-minded delivery—fun fact: his daughter was born the same day he started his role at ServiceNow, underscoring his knack for major life and career milestones coinciding.
11 years of coding experience
9 years of employment as a software developer
University of California Santa Cruz
Github Skills (12)
c1710
databases10
postgresql10
backend10
c1110
postgresql-extension10
graph-database10
back-end-development10
sql10
database10
cypher9
graphdb9
Programming languages (11)
Github contributions (5)
apache/age
Jan 2021 - Jul 2022
Graph database optimized for fast analysis and real-time data processing. It is provided as an extension to PostgreSQL.
Role in this project:
Back-end Developer & Database Engineer
Back-end Developer & Database EngineerContributions:2 releases, 27 reviews, 39 commits in 1 year 5 months
Contributions summary:Josh primarily contributed to the backend development of the Apache AGE graph database extension for PostgreSQL. Their work focused on fixing bugs related to data type casting and error handling within the `agtype` module, which is central to the graph database's functionality. They implemented features such as the `label` function, and enabled use of the agtype datatype for a variety of operations including the use of GIN indices, indicating database-level contributions. Additionally, the user refactored existing code, improved performance for VLE (Variable Length Edge) cases, and implemented the DELETE and MERGE clauses.
analyticsreal-time-datapostgresql-extensionagensgraphdata-processing
JoshInnis/AGE-Machine-Learning
Nov 2021 - Jul 2022
A project that uses Incubating Apache AGE to implment machine learning algorithms
Contributions:51 commits, 2 PRs, 19 pushes in 8 months
incubatingagemachine-learning-algorithmsapachemachine-learning
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