Improve application performance 5x with Automated Caching



Tired of spending months getting your caching right?

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SQL Optimization for your Existing Database

Intelligent SQL Caching

  • Auto-caches into your storage
  • Transparently caches into Amazon Elasticache, Redis, or Hazelcast
  • Auto-invalidation across cache clusters: No more stale data
  • For multiple applications servers accessing a database
  • Custom or packaged apps (e.g. WordPress, Jira, Web apps)

Automated DB Failover

  • Disaster recovery within data centers or geographical regions
  • Today’s failover solutions (e.g. F5 Networks, AWS ELB) result in connection timeouts. 
  • Horizontally scale-out the database without rewriting the application.
  • SQL sharding to data sources.
  • Supports MySQL, SQL Server, Postgres, Amazon RDS, Oracle, DB2

Heimdall Data’s granular SQL analytics helped us identify database inefficiencies and resolve them in a timely manner. The solution was quick to insert into our production environment.

Anthony Galano

Lead Developer,

“Amazon RDS is the most expensive line item in our infrastructure. We reduced our database costs by over 50% with Heimdall Data’s analytics and caching.”

Ka Chan


Heimdall Data’s SQL analytics helped us identify database inefficiencies and resolve them. The all-in-one solution saves us months of development time and operational costs.

Aaron Hayes

Technical Operation Manager, Double Fine Productions

We used Heimdall Data for many projects. In each case, the product was able to root cause the slow database performance. The operational simplicity was unlike any product I have seen in the market.

Global Pharmaceutical Company


Heimdall Data is your “DBA Assistant” offering:

  • SQL auto-caching across application servers removing latency to the database
  • Auto-synchronization across cache nodes
  • Policy-driven horizontal database scale-out
  • No disruption to your existing application or database 
  • Database vendor-neutral (e.g. MySQL, Postgres, Amazon RDS, Oracle, SQL Server, MariaDB)