The Seattle Report on Database Research

Meeting was 2018

What Has Changed in the Last Five Years?

• ML
  • DNN for image analysis and NLP
  • TensorFlow, PyTorch
  • FPGA, GPU
• Data Science: cleaning, transformation, statistics, visualization, and ML.
• Data Governance: GDPR necessitates provenance, metadata management technology, confidential clod computing, ethical and fair use of data...
• Cloud: Usage has grown
  • serverless -- on-demand/high elasticity instead of provisioned resources -- is a thing
  • convergence towards data lake architecture with on-demand analysis via elastic compute (thus: separation of compute and storage)
• IoT: has accelerated
• Hardware:
  • Accelerators: FPGAs, GPUs, ASCIs
  • new SSDs and NVRAM
  • Better bandwidth and latency
    • in datacenter via new interconnects
    • outside via 5G

Research Challenges

Data Science

Instead of OLAP and SQL, Jupyter Notebooks are the new de-facto standard, with an ecosystem of open-source libraries.

Data wrangling is main challenge, focus should be on end-to-end solutions.

Data provenance (Where is the data from? Is it fresh?) is important.

Data Governance

Key motivator: GDPR

Provenance

fixing privacy via cryptography

Ethical data science: the problem of racist AI and Fake news.

Cloud

Similar to the Beckman Report, even though cloud isn't called "cheaper".

Separation of compute & storage

Multi-tenancy

Minimizing lock-in

DB Engines

Heterogeneous Computation becomes important.

Data lakes and modern data warehousing

Dsitributed Transactions

Better benchmarks are required

Two holy grails:

• reduce impedance mismatch between application development and database query
• find way to make db systems less rigid without sacrificing lots of performance

Community

Focus should be real, user-focused open source systems

Less pessimistic / alarmist than the last two reports, maybe they gave up.

Research problems:

• too few people go on PCs
• reproducibility is mediocre
• "new algo vs baseline" papers overvalued compared to papers describing innovative systems, applications, experiments and analyses or user studies.