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ease
features
design
support

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Write a Review

Description

Introducing a unique cloud data lakehouse that is entirely managed and capable of ingesting data from all your sources within minutes, while seamlessly accommodating every query engine at scale, all at a significantly reduced cost. This platform enables ingestion from both databases and event streams at terabyte scale in near real-time, offering the ease of fully managed pipelines. Furthermore, you can execute queries using any engine, catering to diverse needs such as business intelligence, real-time analytics, and AI/ML applications. By adopting this solution, you can reduce your expenses by over 50% compared to traditional cloud data warehouses and ETL tools, thanks to straightforward usage-based pricing. Deployment is swift, taking just minutes, without the burden of engineering overhead, thanks to a fully managed and highly optimized cloud service. Consolidate your data into a single source of truth, eliminating the necessity of duplicating data across various warehouses and lakes. Select the appropriate table format for each task, benefitting from seamless interoperability between Apache Hudi, Apache Iceberg, and Delta Lake. Additionally, quickly set up managed pipelines for change data capture (CDC) and streaming ingestion, ensuring that your data architecture is both agile and efficient. This innovative approach not only streamlines your data processes but also enhances decision-making capabilities across your organization.

Description

Unify all your data sources, encompassing both relational and NoSQL databases, SaaS applications, and APIs, allowing you to query them as if they were a single data entity instantly. Process data at its source without delay, enabling you to query, cache, and merge information from various origins seamlessly. Utilize webhooks to bring in real-time streaming data from platforms like Kafka and Segment into the Peaka BI Table, moving away from the traditional nightly batch ingestion in favor of immediate data accessibility. Approach every data source as though it were a relational database, transforming any API into a table that can be integrated and joined with your other datasets. Employ familiar SQL syntax to execute queries in NoSQL environments, allowing you to access data from both SQL and NoSQL databases using the same skill set. Consolidate your data to query and refine it into new sets, which you can then expose through APIs to support other applications and systems. Streamline your data stack setup without becoming overwhelmed by scripts and logs, and remove the complexities associated with building, managing, and maintaining ETL pipelines. This approach not only enhances efficiency but also empowers teams to focus on deriving insights rather than being bogged down by technical hurdles.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon Redshift Yes 
Amazon S3 Yes 
Apache Cassandra Yes 
Apache Kafka Yes 
Databricks Yes 
Google Cloud BigQuery Yes 
HubSpot CRM Yes 
HubSpot Customer Platform Yes 
Looker Yes 
MongoDB Yes 
MySQL Yes 
Oracle Cloud Infrastructure Yes 
PostgreSQL Yes 
Python Yes 
Salesforce Yes 
Snowflake Yes 
Zendesk Yes 
Zoom Yes 
Firebase No 
Google Drive No 

Integrations

Amazon Redshift Yes 
Amazon S3 Yes 
Apache Cassandra Yes 
Apache Kafka Yes 
Databricks Yes 
Google Cloud BigQuery Yes 
HubSpot CRM Yes 
HubSpot Customer Platform Yes 
Looker Yes 
MongoDB Yes 
MySQL Yes 
Oracle Cloud Infrastructure Yes 
PostgreSQL Yes 
Python Yes 
Salesforce Yes 
Snowflake Yes 
Zendesk Yes 
Zoom Yes 
Firebase Yes 
Google Drive Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

$1 per month
Free Trial Yes 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Onehouse

Country

United States

Website

www.onehouse.ai/

Vendor Details

Company Name

Peaka

Founded

2020

Country

United States

Website

www.peaka.com

Product Features

Data Warehouse

Ad hoc Query No 
Analytics No 
Data Integration No 
Data Migration No 
Data Quality Control No 
ETL - Extract / Transfer / Load No 
In-Memory Processing No 
Match & Merge No 

Product Features

iPaaS

AI / Machine Learning No 
Cloud Data Integration No 
Dashboard No 
Data Quality Control No 
Data Security No 
Drag & Drop No 
Embedded iPaaS No 
Integration Management No 
Pre-Built Connectors No 
White Label No 
Workflow Management No 

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