Launching Graphistry: Visually understand even the most unwieldy data, and try it now in AWS!

Posted by Graphistry Team on Apr 26, 2019

With our big 2.0 release, Graphistry's tech and features have combined into a fast and easy way to connect to your team's data,  visually understand most large or complex problems, and do it all safely & privately. For the first time, you can now easily experience Graphistry from your own AWS account. Read on for what problems our early users are solving, how Graphistry 2.0 is helping them, and quickly getting started in AWS on your own data.


Graphistry's early users are doing incredible things

We're proud of what top data teams have been tackling:

  • Startups like AnChain.AI are investigating $100M+ in fraudulent blockchain transactions
  • Cybersecurity teams in the Fortune 500 and the US government are exposing internal breaches and tracking international hacking groups
  • Infrastructure teams are mapping out live systems to ensure everyone stays safe and running

Their societal scale is stunning:

Every month, top news organizations like the BBC and Al Jeezera have been reporting on their latest results!

 

Graphistry 2.0  unlocks graph analysis on any structured data

We've been a mission on helping users achieve the fastest possible "time to graph insight":

  • Jupyter notebooks pre-installed with sample cookbooks make it easy to try out many data sources. As some examples, you can quickly get going with files like CSVs, log stores like Splunk & ElasticSearch, graph databases like Neo4j and Tigergraph, SQL engines like Databricks (Spark) and BlazingDB (GPU SQL), APIs like AlienVault, NetworkX, AWS Cloudwatch & VPC flow logs,  and  compute frameworks like Nvidia RAPIDS and Python Pandas.vendors
  • Automatic visual graph analytics: Most data isn't a graph... yet. Graphistry's hypergraph transform  automatically turns any CSV or data table into an insightful Graphistry visual graph analytics session. If your data is already in a graph format or database, even easier.
  • 2.0 GPU Engine - Handle big datasets for the first time through automatic GPU acceleration. As a founding member of the GPU Open Analytics Initiative (GOAI) and contributing most of the accelerated web tier of Apache Arrow, our engineers took our already best-in-class GPU graph engine and made it another 5-10X faster and more scalable.   The 2.0 engine combines state-of-the-art technology from our partners like Nvidia RAPIDS and BlazingDB with Graphistry's steadily improving client+cloud GPU technology.

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Animation: Automatically and visually exploring all known protein interactions in the NIH BioGRID database

 

Quickly and easily launch on private data with Graphistry in AWS and Docker

Working with top data teams, we kept hearing two things: make it safe and easy to work in corporate environments.  We're excited to introduce two modes:

  • Get started with secure one-click launch in AWS. By running in your team's AWS account, you can guarantee your data stays private. The one-click launch make setup fast and easy. For teams where procurement or trialing can be a pain, AWS means Graphistry is just part of your existing AWS bill, and you can easily meter use by turning the instance on/off.
  • Go enterprise with Docker. As teams go on-prem and even air-gapped,  easy administration and control becomes critical. Graphistry 2.0 introduces enterprise support such as standard docker-compose yml configurations to help top organizations work in the modern ways that you'd expect.

 

On behalf of our team, we're excited to share Graphistry 2.0 with you. Try it out on your data, and we encourage you to reach out on help getting the most out of it.

 

Happy graphing,

 

- Leo and the full Graphistry team

 

GET STARTED!    SEE THE TUTORIAL