Here’s the difference between Acceldata and Databricks. The comparison is based on pricing, deployment, business model, and other important factors.
Acceldata offers data integration and data streaming solutions. It enables businesses to stream data from Hive, Spark, Tez, MR, Kafka, and HBase, collect and process data, build data clusters, and view actionable insights from the data. It enables businesses to perform root cause analysis, manage anomaly detection, and perform data analysis solutions. The clients include PubMatic, MICHELIN, HEALTHEDGE, etc.
Databricks provides a data lakehouse that unifies your data warehousing and AI use cases on a single platform. With Databricks, you can implement a common approach to data governance across all data types and assets, and execute all of your workloads across data engineering, data warehousing, data streaming, data science, and machine learning on a single copy of the data. Built on open source and open standards, with hundreds of active partnerships, Databricks easily integrates with your modern data stack. Additionally, Databricks uses an open standards approach to data sharing to eliminate ecosystem restrictions. Finally, Databricks provides a consistent data platform across clouds to reduce the friction of multicloud environments. Today, Databricks has over 7000 customers, including Amgen, Walmart, Disney, HSBC, Shell, Grab, and Instacart.
|Categories||Data Quality Monitoring||Data Warehouses, Data Lakes|
|Stage||Early Stage||Late Stage|
|Target Segment||Mid size||Enterprise, Mid size|
|Pricing||Contact Sales||Freemium, Contact Sales|
|Location||California, US||San Francisco, US|
|Companies using it|