Software Alternatives, Accelerators & Startups

Upsolver VS Tamr

Compare Upsolver VS Tamr and see what are their differences

Upsolver logo Upsolver

Upsolver is a robust Data Lake Platform that simplifies big & streaming data integration, management and preparation on premise (HDFS) or in the cloud (AWS, Azure, GCP).

Tamr logo Tamr

Tamr makes data source connectivity and enrichment fast, cost-effective, scalable and accessible to the entire enterprise.
  • Upsolver Landing page
    Landing page //
    2023-08-06
  • Tamr Landing page
    Landing page //
    2023-10-15

Upsolver videos

No Upsolver videos yet. You could help us improve this page by suggesting one.

+ Add video

Tamr videos

Episode 41 - Ramy: Representation vs. Reality | Tareq Tamr

More videos:

  • Review - 【TAMR slime 様】琥珀糖〜Kohakuto Japanese traditional candy〜 slime review【音フェチ】
  • Review - 【TAMR slime様】ポロポロ濃抹茶~Maccha~

Category Popularity

0-100% (relative to Upsolver and Tamr)
Business & Commerce
71 71%
29% 29
Office & Productivity
63 63%
37% 37
Online Services
100 100%
0% 0
Tool
0 0%
100% 100

User comments

Share your experience with using Upsolver and Tamr. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare Upsolver and Tamr

Upsolver Reviews

Top 10 AWS ETL Tools and How to Choose the Best One | Visual Flow
In this way, Upsolver removes the complexity of Big Data and Real-Time projects and reduces their use time from several weeks or months to several hours. With the latest Volcano technology, this tool queries the entire data lake in less than a millisecond and stores 10x the amount of data in RAM.
Source: visual-flow.com

Tamr Reviews

The 28 Best Data Integration Tools and Software for 2020
Description: Tamr offers a machine learning-based data integration product called Unify. The solution allows organizations to connect to any tabular data and publish it anywhere. Users can map schemas with machine learning suggestions and normalize data formats using Spark and SQL. Tamr’s Master Records feature provides a complete view of all entities via simple yes and no...

Social recommendations and mentions

Based on our record, Upsolver seems to be more popular. It has been mentiond 1 time since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Upsolver mentions (1)

  • Anyone Used Dremio?
    Most of the pains of using query engines over object storage are in the ongoing management of files (partitioning, compression, merging many small files into fewer larger files) Cloud data lakes are tremendously valuable when it comes to exploratory and ad-hoc data analysis. If you really require sub-second queries on structured data, you're better off with a data warehouse. I'm not totally clear on your use... Source: almost 3 years ago

Tamr mentions (0)

We have not tracked any mentions of Tamr yet. Tracking of Tamr recommendations started around Mar 2021.

What are some alternatives?

When comparing Upsolver and Tamr, you can also consider the following products

Kylo - Kylo is an end-to-end data lake management software that provides data from many sources in an automated fashion and optimizes it.

Celonis - Celonis offers process mining tool for analyzing & visualizing business processes.

IRI Voracity - IRI Voracity is an automated data management platform that helps you extract, transform and load (ETL) your data lake to any data warehouse or cloud.

UiPath Process Mining - Process mining and execution management software in the cloud that is simple and affordable.

Mozart Data - The easiest way for teams to build a Modern Data Stack

Soroco Scout Platform - Scout Platform is an artificial intelligence bases process mining and execution management software, helps large enterprises, Visualize their entire process in one place with interactive task maps that allow teams to work collaboratively.