
Code42
Symantec Data Loss Prevention
Microsoft BitLocker
Paubox
OpenSSH
GravityZone
Virtru
Arcserve UDP
Amazon EMR
Google BigQuery
Google Cloud Dataflow
Google Cloud Dataproc
Qubole
Snowflake
HortonWorks Data Platform
Databricks
Code42
Amazon EMRAmazon EMR is recommended for data engineers, data scientists, and IT professionals who need to manage and process large datasets in a scalable, efficient, and cost-effective manner. It is especially suitable for businesses that are already using AWS services and want to leverage a tightly integrated ecosystem. Additionally, it is a good choice for organizations that require rapid and flexible data analysis capabilities provided by frameworks such as Hadoop, Spark, HBase, and Presto.
Based on our record, Amazon EMR should be more popular than Code42. It has been mentiond 10 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
It's not a big surprise, given that Code42 (the parent company) pretends they have nothing to do with Crashplan. They've done a massive pivot to some kind of security company, with ZERO references to the OG product of Crashplan on code42.com, which (I'm guessing) is the bulk of their revenue. If you do a site search on google, you'll find some old links, but they just push you over to crashplan.com. Source: about 4 years ago
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: over 3 years ago
I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: about 4 years ago
This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: about 4 years ago
Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 4 years ago
Check out https://aws.amazon.com/emr/. Source: about 4 years ago
Symantec Data Loss Prevention - Fully protect your data with the comprehensive detection technologies and unified policies of Symantec's industry leading Data Loss Prevention (DLP).
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Microsoft BitLocker - BitLocker is a full disk encryption feature included with Windows Vista and later.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Paubox - Paubox provides HIPAA compliant email encryption without the hassle of extra steps.
Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost