Hydrolix transforms the economics of log data

4x MORE DATA

4x LOWER COST

Hydrolix is a streaming data lake that combines decoupled storage, indexed search, and stream processing to deliver real-time query performance at terabyte-scale for a radically lower cost.

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Akamai Technologies [logo], the world's leading distributed content delivery and security company and partner of Hydrolix.
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What is hydrolix?

BENEFITS

Cut your log data retention costs by 75%

Make everyone happy

CFOs love the 4x reduction in data retention costs. Product teams love 4x more data to work with.

Say goodbye to
over-provisioning

Spin up resources when you need them and scale to zero when you don’t.

Achieve greater
control

Fine-tune resource consumption and performance by workload to control costs.

Stress-free data retention

Imagine what you can build when you don’t have to sacrifice data because of budget.

Hydrolix DISRUPTS the economics of log data

THE TECH

Built for terabyte scale log data

Stream processing for log data

Ingest, enrich, and transform log data from multiple sources including Kafka, Kinesis, HTTP.

Return just the data you need, no matter how big your data. Reduce latency and costs, eliminate timeouts, brute force queries.

Decoupled storage

Storage is decoupled from ingest and query, allowing each to independently scale to meet performance, budget targets.

Industry-leading 20x-50x compression

Hydrolix’s high density compression (HDX) typically reduces 1TB of stored data to 55GB.

Keep data on prem

Deploy in your VPC. Eliminate data transfer costs. Maintain tighter security and operational control.

Easy to operatE

Autoscaling, Kubernetes support, and cloud native design make operations at scale a breeze.

WHAT OUR CLIENTS ARE SAYING
  • Blog

    Infographic: 4 Observability Anti-Practices

    Best Practices

    Our new infographic highlights four common observability anti-patterns.

    Franz Knupfer

    I

    May 14, 2024

    2 minute read
    READ MORE
  • Blog

    Dissecting a Hydrolix Query

    Engineering
    Product

    Walk through a Hydrolix query and learn how Hydrolix achieves low latency performance using massive parallelism and sparse indexing.

    Franz Knupfer

    I

    May 7, 2024

    6 minute read
    READ MORE
  • Blog

    Deep Dive: Latest N Rows with Row-Level Partition Pruning

    Engineering
    Product
    Use Cases

    Learn how we optimized the Hydrolix query engine for latest N rows queries through concurrent processing and strategic data handling at scale.

    Federico Rodriguez

    I

    May 1, 2024

    6 minute read
    READ MORE