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  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data Tools
  5. Dremio vs Trino

Dremio vs Trino

OverviewComparisonAlternatives

Overview

Dremio
Dremio
Stacks116
Followers348
Votes8
Trino
Trino
Stacks35
Followers35
Votes0
GitHub Stars12.1K
Forks3.4K

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Detailed Comparison

Dremio
Dremio
Trino
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
Amazon S3
Python
Python
Tableau
Tableau
Azure Database for PostgreSQL
Azure Database for PostgreSQL
Qlik Sense
Qlik Sense
PowerBI
PowerBI
Kafka
Kafka
Prometheus
Prometheus
Druid
Druid
MySQL
MySQL
Elasticsearch
Elasticsearch
MongoDB
MongoDB
PostgreSQL
PostgreSQL
Superset
Superset
Amazon S3
Amazon S3
Clickhouse
Clickhouse

What are some alternatives to Dremio, Trino?

GraphQL

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

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

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

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

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

Presto

Presto

Distributed SQL Query Engine for Big Data

Prisma

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

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

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.

PostGraphile

PostGraphile

Execute one command (or mount one Node.js middleware) and get an instant high-performance GraphQL API for your PostgreSQL database

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