Databricks offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service provides a platform for data pipelines, data lakes, and data platforms.
$0.07
Per DBU
Weka.IO
Score 8.0 out of 10
N/A
WekaIO headquartered in San Jose offers their file system and storage management platform, for multiple storage workloads, supporting AI and computationally intensive workloads and applications.
Databricks is a true all-in-one platform, and at the time of implementation, it had more features available to us, making it a clear choice over Snowflake. Moving our workloads from local computing to the servers in Databricks gave our start-up staff a great quality of life …
Compared to Synapse & Snowflake, Databricks provides a much better development experience, and deeper configuration capabilities. It works out-of-the-box but still allows you intricate customisation of the environment. I find Databricks very flexible and resilient at the same …
The most important differentiating factor for Databricks Lakehouse Platform from these other platforms is support for ACID transactions and the time travel feature. Also, native integration with managed MLflow is a plus. EMR, Cloudera, and Hortonworks are not as optimized when …
Databricks has a much better edge than Synapse in hundred different ways. Databricks has Photon engine, faster available release in cloud and databricks does not run on Open source spark version so better optimization, better performance and better agility and all kind of …
Databricks [Lakehouse Platform (Unified Analytics Platform)] can work with all data types in their original format while Snowflake requires additional structures to fit the data before loading it. Databricks is open source so potential is far greater.
Databricks was picked among other competitors. Closest competition in our organization was H2O.ai and Databricks came out to be more useful for ROI and time to market in our internal research. We could have used AWS products, however Databricks notebooks and ability to launch …
When we started using it, only the notebook experience was mature. However, DB was very helpful giving us direct support to get onto their platform. Really there was little in the way to compare to them at the time. AWS has services but not the same low-cost angle.
I also use Microsoft Azure Machine Learning in parallel with Databricks. They use different file formats which teach me to be flexible and able to write different programs. They are equally useful to me and I would like to master both platforms for any future usage. I do prefer …
We really like that their platform is based on hardware-independent storage, and all Flash. It's exceptionally fast and very easy to use. Almost anyone could use it, as it's very user-friendly, and they in a sense guide you through the process. It's very helpful and helps us …
If you need a managed big data megastore, which has native integration with highly optimized Apache Spark Engine and native integration with MLflow, go for Databricks Lakehouse Platform. The Databricks Lakehouse Platform is a breeze to use and analytics capabilities are supported out of the box. You will find it a bit difficult to manage code in notebooks but you will get used to it soon.
Weka.IO is really well suited for anyone who needs high availability and high-performance computing capabilities with just the click of a button. It has really made us able to provision and replicate applications in the public cloud, and to not spin up a ton of costs from that cloud provider.
First, it handles large amounts of data. We run daily and weekly jobs that process a lot of records. Databricks manages it very well, with no issues, if the cluster is set up properly.
Second, it really works well for incremental updates. We load only new or changed data, which makes it easy to update existing tables without duplicating records.
Third, job scheduling is useful. We can schedule the jobs easily and monitor them. The best part is that we can retry or repair the failed runs.
The last one is about the notebook interface that I really love. It makes development and debugging easy. We can test logic step by step, validate data, and fix all our issues.
Connect my local code in Visual code to my Databricks Lakehouse Platform cluster so I can run the code on the cluster. The old databricks-connect approach has many bugs and is hard to set up. The new Databricks Lakehouse Platform extension on Visual Code, doesn't allow the developers to debug their code line by line (only we can run the code).
Maybe have a specific Databricks Lakehouse Platform IDE that can be used by Databricks Lakehouse Platform users to develop locally.
Visualization in MLFLOW experiment can be enhanced
Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.
in terms of graph generation and interaction it could improve their UI and UX
One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.
We can't really complain about anything with Weka.IO. It works as it should, and we've never had any real issues. We feel they offer the best latency and workload options for the file types that we see the most often. The on-demand scaling is really helpful to our costs.
Databricks is a true all-in-one platform, and at the time of implementation, it had more features available to us, making it a clear choice over Snowflake. Moving our workloads from local computing to the servers in Databricks gave our start-up staff a great quality of life boost.
We really like that their platform is based on hardware-independent storage, and all Flash. It's exceptionally fast and very easy to use. Almost anyone could use it, as it's very user-friendly, and they in a sense guide you through the process. It's very helpful and helps us manage costs very well.