Storage

Purpose-built Storage

Power your mission with efficient data management and retrieval without high cloud costs.

Storage

Benefits

Minimize cloud storage costs

You shouldn’t face a tradeoff between storing data and paying exorbitant cloud bills. Complex hardware requires retention of high frequency data at full fidelity for years. Sift’s storage is object-based, empowering users to selectively keep essential data with precise granular retention and downsampling policies. This ensures efficient data management that allows you to store all the data you need indefinitely — without excessive cloud costs.

Optimized for massive queries

Managing fleets of machines often entails sifting through large volumes of data across multiple telemetry channels, overwhelming most traditional backend storage tools. Sift gives you a fully optimized storage layer that’s built to support advanced exploratory analysis and searching long duration, high cardinality data. Sift overcomes the limitations of traditional options with efficient querying and retrieval that doesn’t compromise on performance.

Integration ready

Telemetry data is valuable and should power all of your team’s operations, and your storage layer should support multiple hardware data types. Sift stores telemetry in an open source format and provides user-friendly APIs to ensure that each customer can hook up their internal tools and algorithms to compressed, high-performance single source of truth.

Features

High cardinality query optimization
Request dozens of telemetry channels without performance degradation

Request dozens of telemetry channels without performance degradation

Asset-level retention and downsampling
Tune storage costs by deciding what telemetry to retain and for how long.

Tune storage costs by deciding what telemetry to retain and for how long.

Open-source interoperable file format
Connect other tools to Sift’s backend to train your AI/ML models or feed your existing workflows

Connect other tools to Sift’s backend to train your AI/ML models or feed your existing workflows

Support for multiple hardware data types/primitives
Send Sift primitives, as well as strings, enums, and bitfields.

Send Sift primitives, as well as strings, enums, and bitfields.

Sift Observability Platform

Missions are complex. Reviewing machine data should be simple.

Ingestion

Scale both the number and complexity of your machines without worrying about ingestion rates.

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Storage

Query a backend that's purpose-built for long duration, high cardinality searches. Add granular retention policies to save only the data you need.

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Visualization

Explore, share, and collaborate with your team — no Python scripts or SQL queries needed. Unify all your data sources in a single window.

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Review

Automatically review simulation, testbed, and operational data. Ingrain your expertise in rules that flag anomalies real-time.

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Reporting

With one-click, generate certification reports for stakeholders. Provide precise access to your data with Role-Based Access Controls.

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FAQs

How does storage work?

The data catalog is stored in PostgreSQL and contains metadata like runs, assets, and channels. Data is persisted to Parquet in batches every few minutes, and real time data is written to the cache for immediate availability. Parquet files are compacted into their optimal size on a recurring basis and as data reaches the end of its retention period.

What data types are supported?

We currently support 10 different data types. Standard ints, floats, and bools, but also strings and enums.

Where do you store the data? Can you store it across international boundaries?

Our goal is to meet customers where they are. If you want to be deployed to a certain cloud environment or have an on-premises deployment, that’s something we can support.

Get a Demo

Contact us today for a no-pressure conversation. Discover what Sift can do for your business.

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