Gaming

Develop compelling features and experiences that capitivate your players

Real-Time Analytics in Gaming

Player engagement is crucial to building successful games. To deepen and maintain engagement, game developers constantly improve game features and experiences, relying heavily on the use of data and real-time analytics to do so.

With Rockset, you can analyze player actions in real time to modify their gaming experiences accordingly or develop new features on that data.

Gaming Use Cases

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    Leaderboards

    Build real-time leaderboards that join data across multiple competitions and time windows. Motivate players to increase their in-game activity in order to compete and advance.
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    Personalization

    Customize gameplay and in-game advertising based on what players are doing in real time. Boost player engagement and conversion with more targeted experiences.
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    Game Analytics

    Use live dashboards to understand what users like, how they interact with game features and how they make purchases. Drive feature decisions to increase retention, conversion and lifetime value.

Why Real-time Analytics in Gaming Is Hard

How Rockset Makes It Easy

Other
Need to join multiple types of gaming data: Games store player profiles, scores, player actions and current game status in different systems. But you can't analyze these data sets together without a lot of data processing work.
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Join data across multiple sources: Join data from different collections and data sources effortlessly. Build more engaging features and customization that rely on multiple types of game data.
Other
No visibility into what players are doing currently: You can't tell what users are doing in real time because user activity streams are sent to data lakes or moved through data pipelines before being analyzed.
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Act on player activity in real time: Rockset ingests data continuously and makes it immediately queryable without any data prep. Elevate user engagement with real-time, adaptive game features.
Other
Can't scale to handle user growth: Query performance suffers as you add more users and accumulate more data, making it challenging to build features that depend on real-time analytics.
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Fast queries at scale: Rockset is optimized to serve low-latency queries at high concurrency. Delight users with snappy, responsive user experiences even as the number of users scales.

Why Real-time Analytics in Gaming Is Hard

Other
Need to join multiple types of gaming data: Games store player profiles, scores, player actions and current game status in different systems. But you can't analyze these data sets together without a lot of data processing work.
Other
No visibility into what players are doing currently: You can't tell what users are doing in real time because user activity streams are sent to data lakes or moved through data pipelines before being analyzed.
Other
Can't scale to handle user growth: Query performance suffers as you add more users and accumulate more data, making it challenging to build features that depend on real-time analytics.

How Rockset Makes It Easy

Check
Join data across multiple sources: Join data from different collections and data sources effortlessly. Build more engaging features and customization that rely on multiple types of game data.
Check
Act on player activity in real time: Rockset ingests data continuously and makes it immediately queryable without any data prep. Elevate user engagement with real-time, adaptive game features.
Check
Fast queries at scale: Rockset is optimized to serve low-latency queries at high concurrency. Delight users with snappy, responsive user experiences even as the number of users scales.
Core Features for Gaming

  • Built-In Data Connectors

    Set up continuous ingestion from common data sources, like MongoDB, DynamoDB, Kafka and S3, in a plug-and play manner. New data is reflected in Rockset in seconds.

  • SQL with JOINs

    Join multiple data sets for analysis. Rockset supports full-featured SQL, enabling complex search, aggregation and join queries.

  • Converged Index™

    Rockset automatically builds search, columnar and row indexes on your data to deliver fast queries at scale.

  • Serverless Autoscaling

    Rockset scales storage, ingest and query layers automatically and independently in response to growth and spikes in usage.

Resources



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