Submissions for Data Stores track

Guide on how to select datastores to solve different problems

This is a call for Submissions for the Data Stores conferences that will be held between September 2021 and August 2022 for the Data Stores track under Rootconf. Choosing Datastores conferences aim to help technology practitioners learn about how to select a datastore and be aware of their limitations when applied to the problem at hand.

We are accepting experiential talks on:

  • 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.

We invite engineers who work closely with datastores to speak about their experience in selecting, using and scaling these technologies.

Contact information: Join the Rootconf Telegram group at or follow @rootconf on Twitter.
For inquiries, contact Rootconf at or call 7676332020.

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Rootconf is a forum for discussions about DevOps, infrastructure management, IT operations, systems engineering, SRE and security (from infrastructure defence perspective). more

Dinesh Dhakal


Migrating Online Data

Submitted Aug 18, 2021

Relational 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 structure of Data at Linkedin, majorly fuelled by the hyper growth phase that the platform has gone through. These structural changes and other performance issues have also required migrating data across schemas, Databases and even different data stores to ensure we keep up with the scale and performance needed to give our members the utmost value.

The key objectives of this talk are -
Discuss the need for Data Migration
Types of Migrations we’ve done at LinkedIn
Strategies for Data Migration for an online Data Store
Planning for the unknowns and Gotchas

Audience Takeaways -

Understand why there might arise a time for Migrating data and it’s the right solution to their problem
How to plan to migrate data within same data store vs across data stores
Learn about the gotchas pitfalls and how to tread them effectively

Session Outline -
Introduction to types of Data Stores (3 mins)
When Data outgrows and underperforms (2 mins)
Do you need to migrate? (3 mins)
Types of Migrations (4 mins)
One shot migration
Trickle Migration
Planning (8 mins)
Understand the data
Define the end goal
Design the components strategically
One must monitor!
Canary, Canary, Canary!
Application support and Cutover
Gotcha! (In Prod!) (3 mins)
Migrating endorsements / Address Book (5 mins)
Conclusion (2 mins)


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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

24 Aug 2021