Dremio vs Trino

Overview

Dremio

Stacks116

Followers348

Votes8

Trino

Stacks35

Followers35

Votes0

GitHub Stars12.1K

Forks3.4K

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PostgreSQL Databases

A powerful, open source object-relational database system

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Detailed Comparison

Dremio	Trino
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.	It is a fast distributed SQL query engine for big data analytics that helps you explore your data universe. It is designed to query large data sets distributed over one or more heterogeneous data sources.
Democratize all your data; Make your data engineers more productive; Accelerate your favorite tools; Self service, for everybody	Highly parallel and distributed query engine; Simplicity; Versatile; In-place analysis
Statistics
GitHub Stars -	GitHub Stars 12.1K
GitHub Forks -	GitHub Forks 3.4K
Stacks 116	Stacks 35
Followers 348	Followers 35
Votes 8	Votes 0
Pros & Cons
Pros 3 Nice GUI to enable more people to work with Data 2 Easier to Deploy 2 Connect NoSQL databases with RDBMS 1 Free Cons 1 Works only on Iceberg structured data	No community feedback yet
Integrations
Amazon S3 Python Tableau Azure Database for PostgreSQL Qlik Sense PowerBI	Kafka Prometheus Druid MySQL Elasticsearch MongoDB PostgreSQL Superset Amazon S3 Clickhouse

What are some alternatives to Dremio, Trino?

GraphQL

GraphQL is a data query language and runtime designed and used at Facebook to request and deliver data to mobile and web apps since 2012.

Google BigQuery

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Amazon Redshift

It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

Qubole

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

Presto

Distributed SQL Query Engine for Big Data

Prisma

Prisma is an open-source database toolkit. It replaces traditional ORMs and makes database access easy with an auto-generated query builder for TypeScript & Node.js.

Amazon EMR

It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.