Likelihood to Recommend 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.
Read full review Datameer is a great tool if someone is capable of keeping the most recent version of the tool up to date along with the most recent version of the distribution of Hadoop. The tool is easy to support but it must have someone who can run the back end processes
Read full review Pros Process raw data in One Lake (S3) env to relational tables and views Share notebooks with our business analysts so that they can use the queries and generate value out of the data Try out PySpark and Spark SQL queries on raw data before using them in our Spark jobs Modern day ETL operations made easy using Databricks. Provide access mechanism for different set of customers Read full review It leverages scalability, flexibility and cost-effectiveness of hadoop to deliver an end-user focused analytic platform for big data without involvement of IT. It overcomes Hadoop`s complexity by providing GUI interface with pre-built functions across integration, analytics and data visualization . Excel feature is awesome for business users which is already provided by Datameer. Using datameer now user can do smart analytic using Decision Trees, Column dependency and recommendation. Recently HTML5 inclusion is making application to available on a wider range of devices, including the iPad and other mobile devices which does not support Flash. It can be used in premise or in a cloud computing environment. Wizard-based data integration designed for IT and business users to schedule and do transformation of large sets of structured, semi-structured and unstructured data without any knowledge of Hadoop ecosystem. Read full review Cons 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 Read full review Concentration issues are possible while using a lot of tabs at once. In most cases, the length of a tutorial video is excessive. A more condensed design is certainly a viable option. Read full review Likelihood to Renew Employees with intermediate SQL and Hive knowledge can generate reports faster than using Datameer . It does have visualization tool but I don't think it is anything that cannot be accomplished by importing the data in Excel
Read full review Usability 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
Read full review Easy to use for most things, starts to require some planning as your projects get more complex.
Mike Blizman Administration of Hadoop cluster - Cloudera, Datameer
Read full review Support Rating 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.
Read full review Alternatives Considered 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 time while
Synapse and
Snowflake feel more limited in terms of configuration and connectivity to external tools.
Read full review Pricing, support, and ease of use. We plan to scale up our data over the net few years and Datameer gives us all the things we need in one tool. Handles large transformations quickly and works with all the cloud data warehouses.
Datameer's per-user pricing sealed the deal for us as we plan to transfer much more data over the next few years. We looked at
Fivetran but the usage pricing discourages growth. We also looked at Informatica but it was too expensive and didn't work as well with other BI tools like Datameer does.
Read full review Return on Investment The ability to spin up a BIG Data platform with little infrastructure overhead allows us to focus on business value not admin DB has the ability to terminate/time out instances which helps manage cost. The ability to quickly access typical hard to build data scenarios easily is a strength. Read full review We have not been able to reach our business objectives just yet. Hadoop its a hard sell in most companies still. Legacy skills are still highly on demand and as long as an easier path leverage SQL for example is available, it would be hard to gain more adoption. Read full review ScreenShots