Software Alternatives, Accelerators & Startups

Azure Synapse Analytics VS Presto DB

Compare Azure Synapse Analytics VS Presto DB and see what are their differences

Azure Synapse Analytics logo Azure Synapse Analytics

Get started with Azure SQL Data Warehouse for an enterprise-class SQL Server experience. Cloud data warehouses offer flexibility, scalability, and big data insights.

Presto DB logo Presto DB

Distributed SQL Query Engine for Big Data (by Facebook)
  • Azure Synapse Analytics Landing page
    Landing page //
    2023-03-23
  • Presto DB Landing page
    Landing page //
    2023-03-18

Azure Synapse Analytics videos

Azure Synapse Analytics - Next-gen Azure SQL Data Warehouse

More videos:

  • Review - Is Azure SQL Data Warehouse the Right SQL Platform for You?

Presto DB videos

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

+ Add video

Category Popularity

0-100% (relative to Azure Synapse Analytics and Presto DB)
Office & Productivity
100 100%
0% 0
Data Dashboard
16 16%
84% 84
Development
100 100%
0% 0
Database Tools
0 0%
100% 100

User comments

Share your experience with using Azure Synapse Analytics and Presto DB. 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 Azure Synapse Analytics and Presto DB

Azure Synapse Analytics Reviews

Top 6 Cloud Data Warehouses in 2023
Azure Synapse analytics is scalable for large data tables based on its distributed computing. It relies on the MPP (mentioned in the beginning, revisit if you did not grasp it) to quickly run high volumes of complex queries across multiple nodes. With Synapse, there’s an extra emphasis on security and privacy.
Source: geekflare.com
Top 5 BigQuery Alternatives: A Challenge of Complexity
Azure SQL Data Warehouse, now subsumed by Azure Synapse Analytics, brings together the worlds of big data analytics and enterprise data warehousing. Over the years, Azure has made a name for enabling the seamless transfer of data between on-premise and cloud ecosystems.
Source: blog.panoply.io

Presto DB Reviews

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

Social recommendations and mentions

Based on our record, Presto DB should be more popular than Azure Synapse Analytics. It has been mentiond 6 times 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.

Azure Synapse Analytics mentions (3)

  • Deploying a Data Warehouse with Pulumi and Amazon Redshift
    A data warehouse is a specialized database that's purpose built for gathering and analyzing data. Unlike general-purpose databases like MySQL or PostgreSQL, which are designed to meet the real-time performance and transactional needs of applications, a data warehouse is designed to collect and process the data produced by those applications, collectively and over time, to help you gain insight from it. Examples of... - Source: dev.to / over 1 year ago
  • [WSJ] Facebook Parent Meta Expected to Post Slowest Revenue Growth Since IPO
    You don't run into these kinds of problems with other tools, like the ones I mentioned. I've never tried the Azure ones, but my gut says they may have some scaling issues (synapse analytics looks promising but I have no experience with it). Source: about 2 years ago
  • The Difference Between Data Warehouses, Data Lakes, and Data Lakehouses.
    Popular managed cloud data warehouse solutions include Azure Synapse Analytics, Azure SQL Database, and Amazon Redshift. - Source: dev.to / about 2 years ago

Presto DB mentions (6)

  • Parsing logs from multiple data sources with Ahana and Cube
    Presto is an open-source distributed SQL query engine, originally developed at Facebook, now hosted under the Linux Foundation. It connects to multiple databases or other data sources (for example, Amazon S3). We can use a Presto cluster as a single compute engine for an entire data lake. - Source: dev.to / about 2 years ago
  • Can a data warehouse be skipped?
    Fair point, but I am talking about Athena (not SQL Server), which under the hood uses a distributed query engine. It is capable to deal with huge amounts of data, if the storage is in the right shape. You can read more about the underlying technology here: https://prestodb.io/. Source: about 2 years ago
  • why use Redshift if we can use S3 to store data and can connect with Quicksight for dashboarding?
    So there is Presto, which is a distributed SQL engine created by Facebook. Source: over 2 years ago
  • Understanding AWS Athena 101
    You can use Athena to run data analytics, with just standard SQL (Presto). - Source: dev.to / almost 3 years ago
  • ETL tool for query building across multiple databases in Mongo DB
    Presto does this, but I'm honestly uncertain how performant it is. In my experience, centralizing data is the superior approach to attempting to query multiple sources in place. Source: almost 3 years ago
View more

What are some alternatives?

When comparing Azure Synapse Analytics and Presto DB, you can also consider the following products

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Databricks Unified Analytics Platform - One platform for accelerating data-driven innovation across data engineering, data science & business analytics

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

Apache Zeppelin - A web-based notebook that enables interactive data analytics.

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Saturn Cloud - ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.