Data is everywhere in the form of values, text, numbers, pictures and so on that can be stored and used anytime when required. The importance of data and data storage systems has gained recognition since businesses find the potential of big data and its use cases. The data was with us always, but the possibilities to use it effectively were an arduous task.
We are pleased to announce the general availability (GA) of Elastic 7.12. This release brings a broad set of new capabilities to our Elastic Enterprise Search, Observability, and Security solutions, which are built into the Elastic Stack — Elasticsearch and Kibana.
We’re thrilled to announce the technical preview of the frozen tier in 7.12, enabling you to completely decouple compute from storage and directly search data in object stores such as AWS S3, Microsoft Azure Storage, and Google Cloud Storage. The next major milestone in our data tier journey, the frozen tier significantly expands your data reach by storing massive amounts of data for the long haul at much lower cost while keeping it fully active and searchable.
Giraffe is InfluxData’s graphing library, built to use and graph the data coming from InfluxData’s time series database, InfluxDB. Yes, there are other graphing libraries available; but ours is the only one purpose-built to graph line protocol without having to convert it. Plus, we have lots of great features, like legends and colorization, without much configuration. So, how to get started?
We’re excited to announce that, as a new entrant in the 2021 Gartner Magic Quadrant for Insight Engines, Elastic has been recognized as a Challenger. You can download the complimentary report today. Read on to learn more about creating powerful, modern search experiences with Elastic Enterprise Search.
Finding relationships between disparate events and patterns can reveal a common thread, an underlying cause of occurrences that, on a surface level, may appear unrelated and unexplainable. The process of discovering the relationships among data metrics is known as correlation analysis. For data scientists and those tasked with monitoring data, correlation analysis is incredibly valuable when used for root cause analysis and reducing time to remediation.
With the volume, velocity, and variety of today’s data, we have all started to acknowledge that there is no one-size-fits-all database for all data needs. Instead, many companies shifted towards choosing the right data store for a specific use case or project. The distribution of data across different data stores brought the challenge of consolidating data for analytics.
