Composable Analytics is a business intelligence solution that provides both cloud-based services and on-premise solutions. Some key features include data flow-based applications, data process automation and application reusability.
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dbt
Score 9.2 out of 10
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dbt is an SQL development environment, developed by Fishtown Analytics, now known as dbt Labs. The vendor states that with dbt, analysts take ownership of the entire analytics engineering workflow, from writing data transformation code to deployment and documentation. dbt Core is distributed under the Apache 2.0 license, and paid Teams and Enterprise editions are available.
I have used number of different products including Yahoo Pipes. There are Enterprise Service Bus (ESB) or Business Intelligence (BI) tools based on ESB that does not quite do the job as Composable Analytics is doing. This product is an innovative product in BI world.
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Chose Composable DataOps Platform
I would compare them to custom system like Morgan Stanley has that I use. A more appropriate company is Novus or LightKeeper. This product is potentially much cheaper but Novus and Lightkeeper already have built in Analytics screens that you could potential build yourself with …
dbt is very flexible and can fit into most data pipelines. This is a pro for most organizations that aren't fully bought into one platform (Google Cloud, etc.)
Matillion is graphical versus dbt, which is SQL code-based (that, of course, is a matter of personal preference and not an objective advantage). The integrated testing, documentation generation, lineage, etc., were additional criteria that led us to choose dbt.
I actually don't know what the alternative to dbt is. I'm sure one must exist other than more 'roll your own' options like Apache Airflow, say, bu tin terms of super easy managed/cloud data transforms, dbt really does seem to be THE tool to use. It's $50/month per dev, BUT …
Snaplogic is great at the Extraction and Load processes of ETL. It can pull data from anywhere, even behind firewalls. So if you need to get data from various APIs, databases, files, S3, SFTP, etc it is easy to do so. However, it requires special knowledge in order to build …
Most ETL pipeline products have a T layer, but dbt just does it better. The transformation is on steroids compared to the others. Also, just allows much more Adhoc solutions for very specific projects. Those ETL tools are probably better on the T part if you don't need too many …
Airflow can accomplish the same work as dbt (data build tool), however, dbt's (data build tool) development workflow and UI can open up data transformation and modeling work to non-data engineering teams. Looker might also be able to define data models via LookML with a …
Composable Analytics is a well suited application when you need to gain insight on many different sources of information. It is less appropriate if you are trying to use it as an application only instead of a tool to create insight into your data.
dbt (Data Build Tool) is best suited for doing the data transformation. dbt is just a transformation tool and it is not suitable for building a data pipeline which requires extraction of data and loading. dbt is well suited for SQL based transformation logic and it is less appropriate when transformation logic requires python.
Slow load times of the dbt cloud environment (they're working on it via a new UI though)
More out-of-the-box solutions for managing procedures, functions, etc would be nice to have, but honestly, it's pretty easy to figure out how to adapt dbt macros
dbt is very easy to use. Basically if you can write SQL, you will be able to use dbt to get what you need done. Of course more advanced users with more technical skills can do more things.
I would compare them to custom system like Morgan Stanley has that I use. A more appropriate company is Novus or LightKeeper. This product is potentially much cheaper but Novus and Lightkeeper already have built in Analytics screens that you could potential build yourself with Composable.
Matillion is graphical versus dbt, which is SQL code-based (that, of course, is a matter of personal preference and not an objective advantage). The integrated testing, documentation generation, lineage, etc., were additional criteria that led us to choose dbt.