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Advice on Dremio and Segment

We need to perform ETL from several databases into a data warehouse or data lake. We want to

  • keep raw and transformed data available to users to draft their own queries efficiently
  • give users the ability to give custom permissions and SSO
  • move between open-source on-premises development and cloud-based production environments

We want to use inexpensive Amazon EC2 instances only on medium-sized data set 16GB to 32GB feeding into Tableau Server or PowerBI for reporting and data analysis purposes.

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Replies (3)
John Nguyen
Recommends
on
AirflowAirflowAWS LambdaAWS Lambda

You could also use AWS Lambda and use Cloudwatch event schedule if you know when the function should be triggered. The benefit is that you could use any language and use the respective database client.

But if you orchestrate ETLs then it makes sense to use Apache Airflow. This requires Python knowledge.

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Recommends
on
AirflowAirflow

Though we have always built something custom, Apache airflow (https://airflow.apache.org/) stood out as a key contender/alternative when it comes to open sources. On the commercial offering, Amazon Redshift combined with Amazon Kinesis (for complex manipulations) is great for BI, though Redshift as such is expensive.

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Recommends

You may want to look into a Data Virtualization product called Conduit. It connects to disparate data sources in AWS, on prem, Azure, GCP, and exposes them as a single unified Spark SQL view to PowerBI (direct query) or Tableau. Allows auto query and caching policies to enhance query speeds and experience. Has a GPU query engine and optimized Spark for fallback. Can be deployed on your AWS VM or on prem, scales up and out. Sounds like the ideal solution to your needs.

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karunakaran karthikeyan
Needs advice
on
DremioDremio
and
TalendTalend

I am trying to build a data lake by pulling data from multiple data sources ( custom-built tools, excel files, CSV files, etc) and use the data lake to generate dashboards.

My question is which is the best tool to do the following:

  1. Create pipelines to ingest the data from multiple sources into the data lake
  2. Help me in aggregating and filtering data available in the data lake.
  3. Create new reports by combining different data elements from the data lake.

I need to use only open-source tools for this activity.

I appreciate your valuable inputs and suggestions. Thanks in Advance.

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Replies (1)
Rod Beecham
Partnering Lead at Zetaris · | 3 upvotes · 63.1K views
Recommends
on
DremioDremio

Hi Karunakaran. I obviously have an interest here, as I work for the company, but the problem you are describing is one that Zetaris can solve. Talend is a good ETL product, and Dremio is a good data virtualization product, but the problem you are describing best fits a tool that can combine the five styles of data integration (bulk/batch data movement, data replication/data synchronization, message-oriented movement of data, data virtualization, and stream data integration). I may be wrong, but Zetaris is, to the best of my knowledge, the only product in the world that can do this. Zetaris is not a dashboarding tool - you would need to combine us with Tableau or Qlik or PowerBI (or whatever) - but Zetaris can consolidate data from any source and any location (structured, unstructured, on-prem or in the cloud) in real time to allow clients a consolidated view of whatever they want whenever they want it. Please take a look at www.zetaris.com for more information. I don't want to do a "hard sell", here, so I'll say no more! Warmest regards, Rod Beecham.

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Pros of Dremio
Pros of Segment
  • 3
    Nice GUI to enable more people to work with Data
  • 2
    Connect NoSQL databases with RDBMS
  • 2
    Easier to Deploy
  • 1
    Free
  • 86
    Easy to scale and maintain 3rd party services
  • 49
    One API
  • 39
    Simple
  • 25
    Multiple integrations
  • 19
    Cleanest API
  • 10
    Easy
  • 9
    Free
  • 8
    Mixpanel Integration
  • 7
    Segment SQL
  • 6
    Flexible
  • 4
    Google Analytics Integration
  • 2
    Salesforce Integration
  • 2
    SQL Access
  • 2
    Clean Integration with Application
  • 1
    Own all your tracking data
  • 1
    Quick setup
  • 1
    Clearbit integration
  • 1
    Beautiful UI
  • 1
    Integrates with Apptimize
  • 1
    Escort
  • 1
    Woopra Integration

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Cons of Dremio
Cons of Segment
  • 1
    Works only on Iceberg structured data
  • 2
    Not clear which events/options are integration-specific
  • 1
    Limitations with integration-specific configurations
  • 1
    Client-side events are separated from server-side

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What is Dremio?

Dremio—the data lake engine, operationalizes your data lake storage and speeds your analytics processes with a high-performance and high-efficiency query engine while also democratizing data access for data scientists and analysts.

What is Segment?

Segment is a single hub for customer data. Collect your data in one place, then send it to more than 100 third-party tools, internal systems, or Amazon Redshift with the flip of a switch.

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What are some alternatives to Dremio and Segment?
Presto
Distributed SQL Query Engine for Big Data
Apache Drill
Apache Drill is a distributed MPP query layer that supports SQL and alternative query languages against NoSQL and Hadoop data storage systems. It was inspired in part by Google's Dremel.
Denodo
It is the leader in data virtualization providing data access, data governance and data delivery capabilities across the broadest range of enterprise, cloud, big data, and unstructured data sources without moving the data from their original repositories.
AtScale
Its Virtual Data Warehouse delivers performance, security and agility to exceed the demands of modern-day operational analytics.
Snowflake
Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
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