Integrate Cassandra with Mention
The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance. Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. Cassandra’s support for replicating across multiple datacenters is best-in-class, providing lower latency for your users and the peace of mind of knowing that you can survive regional outages.
Mention monitors conversations about a brand by tracking any time that the brand is mentioned on a range of online platforms, including social media, blogs, or news outlets. Mention can then analyze the sentiment of those conversations and send that information to users in the form of alerts. This data also allows Mention to gauge overall public sentiment and reputation of a brand. If those metrics seem particularly unusual - i.e. if there is a spike in negative public sentiment - they can send notifications immediately so that changes can be made.
Popular Use Cases
Bring all your Cassandra data to Amazon Redshift
Load your Cassandra data to Google BigQuery
ETL all your Cassandra data to Snowflake
Move your Cassandra data to MySQL
Bring all your Mention data to Amazon Redshift
Load your Mention data to Google BigQuery
ETL all your Mention data to Snowflake
Move your Mention data to MySQL
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Mention's End Points
Create or modify a Mention user account, including the user’s contact info, how often they receive alerts and what kind of access they have to the data on Mention. This allows you to ensure that users can operate as efficiently as possible and interact with Mention in a way that creates the best workflow for them.
Retrieve a list of mentions that have been tracked by your alerts, which can be filtered by a number of parameters including source, date range and tone. This query then returns details - like description, source and author’s influence score - about the relevant mentions, allowing you to gauge if the mention warrants a response.
Define the parameters of an alert, such as the alert’s name, query terms and tracked sources. Then, retrieve data about the mentions that have triggered the alert, including how many mentions there are and how important it is to respond to them.
Design tags, which can be used to filter responses generated by your alerts. Once a tag is created, you can either fetch all the Mentions with that tag in them or use the tag as one of many parameters to filter queries about the mentions in an alert.