We have worked on solving the problem of large-scale data ingestion to a data lake for analysis longer than we care to admit. Initially, we were building a columnar database that was designed to scale on ingestion and analytics across hundreds of Linux nodes.
This was the answer to big data at the largest enterprises who were struggling with the torrent of data from the proxy, firewalls, Windows, Netflows, and other high velocity sources. However, running multiple clusters with proprietary software was limiting our ability to scale and to leverage new capabilities from the open-source communities. We also learned that too many components in the backend database, as is the case with Elasticsearch and Hadoop, introduced complexity and did not bring us any closer to an easy-to-use and cost-effective solution. It was also clear that this type of architecture did not translate well in a cloud environment.
We built our solution on Snowflake for a very simple reason. Snowflake’s philosophy resonated deeply with us and it became clear that we were working towards the same goals: Enable organizations to have seamless access to explore, share, and unlock data value with the mission to break down data silos. The Snowflake platform proved to be ideal for Observability applications with its five fundamental characteristics:
- Single scalable data store for data across use cases
- High performance
- Utility pricing model (customers pay only for the resources they consume)
- Instant compute Elasticity
- Ease of use
We have squeezed every single benefit from the Snowflake platform and, with our data pipeline, machine learning-based analytics, correlation, search, and dashboards, can offer a solution that finally shows the true potential of what “the Cloud” can do for better observability and, ultimately, a better run business for all our customers. Join Elysium Analytics in the Observability revolution.
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