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Upsolver VS Dremio

Compare Upsolver VS Dremio and see what are their differences

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).

Rating
0 reviews
Alternatives Is it good?
Dremio

Get more value from your data, faster. Dremio makes your data engineers more productive, and your data consumers more self-sufficient.

Rating
0 reviews
Pricing
Open source
Alternatives Is it good?
Axcrypt
AxCrypt is a powerful, easy-to-use encryption tool that protects your files, passwords, and personal information with strong AES-256 security. Available on Windows, Mac, Android, and iOS, it keeps your data safe wherever you go. sponsored

Which is more popular?

Based on our record, Upsolver seems to be more popular. It has been mentioned 1 time since March 2021.

social mentions
1 vs 0
Office & Productivity popularity
53% vs 47%
alternatives listed
37 vs 52

Base details

Website, pricing, platforms and company facts side by side.

Upsolver
Dremio
Website upsolver.com dremio.com
Pricing
Official pricing
Open source
Company — Startup from the United States · 100 - 249 employees · 2015
Listed in
Business & Commerce Office & Productivity Online Services Security & Privacy +1
Business & Commerce Office & Productivity Online Services Security & Privacy +1

Features and specs

What each product offers, as listed by its team.

Upsolver 5 features
Dremio 5 features
  • Ease of Use
    Upsolver provides a user-friendly interface, making it accessible for users with varying levels of technical expertise. It simplifies complex data processing tasks, reducing the need for extensive coding knowledge.
  • Real-time Data Processing
    Upsolver is specifically designed for real-time data ingestion and processing. This capability allows businesses to react quickly to new data and gain timely insights.
  • Integration Capabilities
    Upsolver supports integration with a wide range of data sources and destinations, including AWS services, databases, and data lakes, enhancing its flexibility and utility across various data ecosystems.
  • Scalability
    The platform can scale to handle large volumes of data without significant performance degradation, making it suitable for enterprise-grade applications.
  • Serverless Architecture
    Being serverless, Upsolver eliminates the need for infrastructure management, allowing users to focus more on data processing and analytics rather than on maintenance.

Possible disadvantages

  • Cost
    While Upsolver offers powerful features, they come at a premium price, which might be a concern for small to medium-sized businesses with limited budgets.
  • Learning Curve
    Despite its user-friendly interface, there can still be a learning curve for users unfamiliar with data processing principles or the specific paradigms Upsolver employs.
  • Dependency on Cloud Providers
    Upsolver is heavily integrated with cloud services, particularly AWS, which might not be ideal for organizations looking for multi-cloud or on-premises solutions.
  • Limited Customizability
    For very specific or advanced use cases, Upsolver might not offer the level of customizability that a fully hand-coded solution would provide.
  • Support and Documentation
    While Upsolver provides customer support and documentation, some users have reported that the documentation can be insufficient for complex implementations, potentially requiring additional support.
  • Data Virtualization
    Dremio provides powerful data virtualization capabilities that enable users to query data across multiple sources without physical data movement.
  • Performance Acceleration
    Utilizes in-memory processing and Apache Arrow for high-speed data access and query performance, reducing the time to insights.
  • User-Friendly Interface
    Offers a user-friendly web UI that allows data engineers and analysts to manage data sources and create datasets without deep technical expertise.
  • Open Source Foundation
    Dremio is built on an open-source platform, fostering community-driven development and transparency.
  • No ETL Required
    Eliminates the need for traditional ETL processes by allowing direct querying from original data sources, which can lead to cost and time savings.

Possible disadvantages

  • Complex Setup
    Initial setup and configuration can be complex, especially when integrating with a wide variety of data sources and environments.
  • Resource Intensive
    Dremio can be resource-intensive, requiring significant memory and processing power, which could be challenging for smaller infrastructures.
  • Learning Curve
    There can be a steep learning curve for users unfamiliar with SQL-based analytics or Dremio's specific functionalities.
  • Limited Offline Support
    May have limited offline capabilities, which can be a drawback in environments where constant online access isn't guaranteed.
  • Dependency on Community Support
    While open-source platforms are advantageous, they also rely heavily on community support for troubleshooting and updates, which can be less predictable than commercial alternatives.

Analysis

An editorial look at what each product does well and who it suits.

Upsolver
Dremio

Overall verdict

  • Overall, Upsolver is considered a good solution for organizations looking to streamline their data processing workflows without investing heavily in custom engineering. It provides a practical combination of features that make big data processing accessible and efficient.

Why this product is good

  • Upsolver is known for its ease of use and capability to handle large volumes of event data in real-time. It simplifies the process of transforming and analyzing data streams by providing a no-code/low-code platform. This reduces the need for extensive engineering resources, making it accessible to data teams of varying sizes and skill levels. Additionally, it integrates well with popular data lakes and warehouses, enhancing its versatility.

Recommended for

  • Data teams that lack extensive engineering resources.
  • Organizations that require real-time data processing capabilities.
  • Businesses utilizing cloud data lakes or warehouses.
  • Companies looking to simplify ETL processes with minimal coding.

No analysis of Dremio yet.

Videos

Walkthroughs and reviews on video.

Upsolver 0 videos + Add
Dremio 3 videos + Add

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

Introduction to Self-Service Data with Dremio

More videos

  • - Data Access for Data Science | Dremio
  • - Dremio Demo | Deploying Dremio AWS Edition Step-by-Step

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Upsolver
Dremio
53% 53%
Office & Productivity
47% 47%
56% 56%
Online Services
44% 44%
56% 56%
Business & Commerce
44% 44%
100% 100%
Data Dashboard
0% 0%

User comments

Share your experience with using Upsolver and Dremio. For example, how are they different and which one is better?

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Reviews and articles

External articles and on-site reviews we used to compare the two products.

Upsolver no reviews yet
Dremio no reviews yet

We have no reviews of Dremio yet. Be the first one to post

Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Upsolver 1 mention
Dremio 0 mentions
  • 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... Source: about 5 years ago

Tracking Dremio since Mar 2021.

Alternatives to Upsolver and Dremio

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

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