Enabling the high potential of IoT in life sciences
The Challenge
IoT can transform the world of life sciences and, in doing so, radically improves healthcare outcomes. Efficiencies and insights from IoT are already helping to improve lives.
The promise of IoT is more data – and, more importantly, the insights that data brings. Life sciences are now on track to become the fastest-growing segment of the entire IoT market. Annual compound growth of over 15%, no less.1
Today, life science professionals have many data points at their fingertips and with the right tools can speed up innovations and discoveries.
The Solution
CrateDB enables organisations to make the most out of the complexity of smart data and can be an integral part of digital innovation across every level of the life sciences value chain, from R&D to manufacturing.Our distributed database technology improves the flow of information going into data systems, while our next-generation management software optimises the insights delivered.
Resources
WEBINAR
The design of a time-series database
Best practices for working with time-series data fast, with horizontal scalability, and with SQL.
EBOOK
CrateDB Customer Success Stories
Big Data made simple: One single hub for all your operational data insights. Learn how our clients harnessed the full value of their operational data with CrateDB
WHITE PAPER
Time-series data in manufacturing
Interested in industrial time-series? This white paper answers all your questions, diving deep into the topic.
COMPARING DATABASES
CrateDB vs others
Find out how CrateDB compares to databases like MongoDB, TimescaleDB or InfluxDB
GET STARTED
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Get started with CrateDB Cloud and launch a 30-day trial cluster.
Designed to handle the complexity of high-end time series workloads in real-time, CrateDB Cloud is a fully managed database-as-a-service. Secured, scaled and operated by the engineers that built CrateDB.
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CrateDB is the leading open source, distributed SQL database for relational and time‑series data. It combines the familiarity of SQL with the scalability and data flexibility of NoSQL.