Datastreamer vs. Panoply

Datastreamer has great competency in aggregation and classification of large amounts of unstructured, conversational/social data. We perform media monitoring on social media data which is infinitely large and changing every second. Datastreamer is able to stream that high volume of complex data reliably. There are other solutions better suited for small data movement efforts. The AI models and operations set Datastreamer apart from simple web API's that only collect data and pass it on without augmenting it's value. Very appropriate for organizations looking to use this type of information to understand and classify sentiment, identify themes/insights to assist in decision making across multi-department roles in an organization: PR, marketing, security etc.

Panoply is great for smaller organizations where analytics is critical, but it is unrealistic to hire a data engineer or build a data infrastructure. Panoply comes as a full data stack out of the box.

• Redshift setup -- so much easier with Panoply, rather than messing around with AWS mishegoss
• Automated data ingestion and formatting -- I love not having to write out SQL table schema
• Easy scaling and data warehouse maintenance -- I don't like to have to mess with this in previous redshift implementations

• Needs more user control

It’s a good choice for building a quick, multipurpose data stack for a variety of businesses needs.

Panoply has much more storage and better organization tools for searching. There are better folders and tools for keeping documents secure and stored for a long period of time. It is better to offload data in mass than singular or Zip drive documents like you would do in Google Drive.

Incentivized

• The user interface could use some improvement for analytical tools. Apart from that, it’s great.