Audience
Individuals & companies looking for an open source platform that collects, stores and allows them to analyze sensor data
About Warp 10
Warp 10 is a modular open source platform that collects, stores, and analyzes data from sensors.
Shaped for the IoT with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series).
Warp 10 is both a time series database and a powerful analytics environment, allowing you to make: statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts.
The analysis environment can be implemented within a large ecosystem of software components such as Spark, Kafka Streams, Hadoop, Jupyter, Zeppelin and many more. It can also access data stored in many existing solutions, relational or NoSQL databases, search engines and S3 type object storage system.
Pricing
Free Version:
Free Version available.
Integrations
Company Information
SenX
Founded: 2013
France
warp10.io
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VictoriaMetrics
VictoriaMetrics is a fast and scalable open source time series database and monitoring solution. It's designed to be user-friendly, allowing users to build a monitoring platform without scalability issues and with minimal operational burden.
VictoriaMetrics is ideal for solving use cases with large amounts of time series data for IT infrastructure, APM, Kubernetes, IoT sensors, automotive vehicles, industrial telemetry, financial data, and other enterprise-level workloads.
VictoriaMetrics is powered by several components, making it the perfect solution for collecting metrics (both push and pull models), running queries, and generating alerts.
With VictoriaMetrics, you can store millions of data points per second on a single instance or scale to a high-load monitoring system across multiple data centers. Plus, it's designed to store 10x more data using the same compute and storage resources as existing solutions, making it a highly efficient choice.
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Waylay
Modular IoT platform providing best-of-breed OEM technology for back-end development and operations, enabling accelerated IoT solution delivery at scale. Advanced rule logic modeling, execution and lifecycle management. Automate any data workflow, from the simple to the complex. The Waylay platform is built from the ground up to natively cope with the multiple data patterns of IoT, OT and IT. Leverage streaming and time series analytics within the same collaborative intelligence platform. Accelerate the time to market of your IoT solutions by easily delivering self-service and KPI-centric apps to non-developer teams. Find out what automation tools are best suited to your IoT use case, then test them against the benchmark. IoT application development is fundamentally different from “normal” IT development. It requires bridging the physical world of Operations Technology (OT) with sensors, actuators and gateways to the digital world of Information Technology (IT) with databases.
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Amazon Timestream
Amazon Timestream is a fast, scalable, and serverless time series database service for IoT and operational applications that makes it easy to store and analyze trillions of events per day up to 1,000 times faster and at as little as 1/10th the cost of relational databases. Amazon Timestream saves you time and cost in managing the lifecycle of time series data by keeping recent data in memory and moving historical data to a cost optimized storage tier based upon user defined policies. Amazon Timestream’s purpose-built query engine lets you access and analyze recent and historical data together, without needing to specify explicitly in the query whether the data resides in the in-memory or cost-optimized tier. Amazon Timestream has built-in time series analytics functions, helping you identify trends and patterns in your data in near real-time.
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QuestDB
QuestDB is a relational column-oriented database designed for time series and event data. It uses SQL with extensions for time series to assist with real-time analytics. These pages cover core concepts of QuestDB, including setup steps, usage guides, and reference documentation for syntax, APIs and configuration. This section describes the architecture of QuestDB, how it stores and queries data, and introduces features and capabilities unique to the system. Designated timestamp is a core feature that enables time-oriented language capabilities and partitioning. Symbol type makes storing and retrieving repetitive strings efficient. Storage model describes how QuestDB stores records and partitions within tables. Indexes can be used for faster read access on specific columns. Partitions can be used for significant performance benefits on calculations and queries. SQL extensions allow performant time series analysis with a concise syntax.
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Product Details
Platforms Supported
SaaS
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