Submissions for Data Stores track
Guide on how to select datastores to solve different problems
Accepting submissions
Not accepting submissions
We are accepting experiential talks and written content on:
- Performance tuning
- Data migration
- Hidden criteria of database selection such as operations or impact on other teams within an organization such as data platform teams.
- Data modelling and developer experience with datastore.
- Running datastores at scale - the true meaning of tuning, debugging and operations.
- Solving specific use cases with a certain datastore.
- DatastoreOps workflows.
- Use of datastore in novel ways to solve for legal regulations.
Content can be submitted in the form of:
- 15 minute talks
- 30 minute talks
- 1,000 word written articles
Submissions will be peer-reviewed by the editor Yagnik Khanna.
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JM
Jatin K Malik Optimising configurations @ Uber with dual store strategyMost of the software services are driven by internal configurations. There is no one-size-fits-all solution for these configurations as they could be as simple as some basic flags to full-blown multi-page JSONs. One common pitfall across these services is that the configurations are hardcoded in the codebase as JSON, YAML files. Customizations are hard to maintain, difficult to change, and prohib… more
Category: 30 min talk
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DD
Dinesh Dhakal Migrating Online DataRelational Databases as well as non relational data stores support a number of high performing, high volume and highly available applications on the Internet. At Linkedin, many important functionalities are powered by an RDBMS (MySQL and Oracle) or a NoSQL Data Store (Espresso). While we’ve developed a reliable process for schema evolution, we have also run into major changes in the fundamental s… more
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AS
Amandeep Singh When, why and what database to choose for time-series data analytics?Introduction Time series database (TSDB) is optimized for storing and serving data through associated pairs of time and value. They are different from other datastores that track changes to the overall system as INSERTs not UPDATEs. TSDB largely help in forecasting and anomaly detection with seamless application of moving average, exponential smoothing, stationarity, autocorrelation, SARIMA, and … more
Category: 15 min talk
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