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What is rakam?

Rakam provides customized reporting solutions for diverse teams, ensuring that no group is limited to a single user interface. It effortlessly translates queries made within its interface into SQL commands, making it easier for end-users to interact with the data. Notably, Rakam does not move any data into your data warehouse; it works on the premise that all essential information is already present there, facilitating direct analysis from the warehouse, which serves as your ultimate source of truth. For additional information on this topic, be sure to explore our blog post. Furthermore, Rakam integrates with dbt core, acting as the data modeling layer without executing your dbt transformations. Instead, it links to your GIT repository to keep your dbt models updated automatically. In addition, Rakam can create incremental dbt models, boosting query efficiency while reducing database expenses. By specifying aggregates within your dbt resource files, Rakam efficiently generates roll-up models, which streamlines the process for users and promotes effective data management. This efficient approach enables teams to concentrate on deriving insights rather than getting bogged down by the technical complexities of data analysis, ultimately enhancing productivity.

What is nao?

Nao is a cutting-edge integrated development environment for data that utilizes artificial intelligence, crafted specifically for data teams, effectively combining a coding interface with immediate access to your data warehouse. This platform allows for the writing, testing, and management of data-related code while ensuring complete contextual awareness, and it supports a diverse range of data warehouses, including Postgres, Snowflake, BigQuery, Databricks, DuckDB, Motherduck, Athena, and Redshift. Once connected, Nao elevates the traditional data warehouse console by introducing features such as schema-aware SQL auto-completion, data previews, SQL worksheets, and simple navigation across multiple data warehouses. Central to Nao is its intelligent AI agent, which possesses an in-depth understanding of your data schema, including tables, columns, metadata, and the surrounding context of your codebase or data stack. This AI agent is adept at generating SQL queries, building complete data transformation models akin to those in dbt workflows, refactoring existing code, refreshing documentation, executing data quality checks, and running data-diff tests. Additionally, it has the capability to reveal insights and support exploratory analytics, all while rigorously upholding data structure and quality standards. With its extensive features, Nao not only simplifies workflows for data teams but also significantly boosts their productivity and efficiency in managing data operations. This innovative approach fundamentally transforms how data professionals interact with and leverage their data resources.

Media

Media

Integrations Supported

Amazon Redshift
Google Cloud BigQuery
PostgreSQL
Snowflake
ClickHouse
Firebase
Google Analytics 360
MySQL
Presto
Snowplow Analytics
Tenjin

Integrations Supported

Amazon Redshift
Google Cloud BigQuery
PostgreSQL
Snowflake
Amazon Athena
Amazon Bedrock
GitHub
MotherDuck
Obsidian
Omni
OpenAI
SQL
Tableau

API Availability

Has API

API Availability

Pricing Information

$25 per user per month
Free Version

Pricing Information

$30 per month
Free Version
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

Windows
Mac

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Rakam

Date Founded

2016

Company Location

United States

Company Website

rakam.io

Company Facts

Organization Name

nao

Company Location

United States

Company Website

getnao.io

Categories and Features

Digital Analytics

Not specified

Product Analytics

Not specified

Categories and Features

AI Data Analytics

Not specified

IDE

Not specified

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