DremioWhat is Dremio?
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.
Dremio is a tool in the Databases category of a tech stack.
Key Features
Democratize all your dataMake your data engineers more productiveAccelerate your favorite toolsSelf service, for everybody
Dremio Pros & Cons
Pros of Dremio
- ✓Nice GUI to enable more people to work with Data
- ✓Connect NoSQL databases with RDBMS
- ✓Easier to Deploy
- ✓Free
Cons of Dremio
- ✗Works only on Iceberg structured data
Dremio Alternatives & Comparisons
What are some alternatives to Dremio?
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.
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.
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.
