Telco analytics for real time location based services & maintenance


As cell phone usage skyrockets around the world and Telco network coverage becomes a commoditized feature for most consumers, Telco companies are racing to mine insights from cell phone towers to help improve quality of service, improve customer experience, reduce congestion and use predictive maintenance to avoid dead cell towers. To do this, they have to capture statistics such as dropped calls, detect dead zones in coverage, identify and proactively deal with handset issues from inspecting network data and optimize the network for better delivery of voice and data.


  • High data volumes, which makes optimized ingestion important
  • Custom protocols that need to be converted/preprocessed
  • Constant updates and need for high availability
  • Complex SQL queries and need to update analytic dashboards in real time


The leading Telco provider in Philippines is using SnappyData to provide mission critical infrastructure for Telco applications that need data high availability, high concurrency for client applications, both OLTP and OLAP querying and cross data center replication of data over the WAN. Data volumes for operational data is in the terabyte range

Snappy Capabilities in Use

  • Optimized data ingestion
  • In memory row and column table updates and appends
  • Distributed Transactions
  • Redundancy and HA
  • Stream processing
  • OLTP and OLAP SQP querying
  • Cross data center replication over WAN

The Apache Spark Database

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