snappydata.io

SnappyData - The Spark Database

SnappyData is a high performance in-memory data platform for mixed workload applications. Built on Apache Spark, SnappyData provides a unified programming model for streaming, transactions, machine learning and SQL Analytics in a single cluster.
traffic

OVERVIEW

This domain snappydata.io currently has an average traffic classification of zero (the lower the more users). We have evaluated zero pages within the website snappydata.io and found two websites linking to snappydata.io. There are four mass web sites possessed by this website.
Links to this site
2
Social Links
4

SNAPPYDATA.IO RANKINGS

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LINKS TO BUSINESS

Schejter Lior Schejter et al

Doing something I generally love doing. I work as an architect, but occasionally dabble in programming on side projects. Can be seen on LinkedIn, some of my previous work is also referenced here.

WHAT DOES SNAPPYDATA.IO LOOK LIKE?

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SNAPPYDATA.IO HOST

We identified that a single root page on snappydata.io took four thousand four hundred and sixty-nine milliseconds to come up. I could not find a SSL certificate, so therefore our parsers consider this site not secure.
Load time
4.469 seconds
SSL
NOT SECURE
Internet Address
54.243.85.55

SERVER OPERATING SYSTEM

I discovered that this domain is using the Cowboy os.

TITLE

SnappyData - The Spark Database

DESCRIPTION

SnappyData is a high performance in-memory data platform for mixed workload applications. Built on Apache Spark, SnappyData provides a unified programming model for streaming, transactions, machine learning and SQL Analytics in a single cluster.

CONTENT

This domain snappydata.io has the following in the web page, "Joining a Billion Rows 20x Faster than Spark." Our analyzers observed that the webpage also stated " SnappyData, the Spark Database." The Website also stated " Stream - Transact - Analyze - Predict all in one cluster. With an Apache V2 license. Using a number of OLAP optimizations, SnappyData improves on the performance of Spark. Unify real-time and static data sources. Ingest streams, transactional data, NoSQL, SQL, HDFS, CSV, S3, JSON and access via SQL or the Spark API. For the big data audience."

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