Data Warehousing

Alooma makes it easy to use your data warehouse of choice. Whether it's ad-hoc analysis, machine learning, data science, or operational analytics, Alooma lets you look past the pipeline for real insights, fast.

Data warehousing made easy

Connect to your data warehouse of choice to extract actionable insights or access your raw data directly.
Stream to any popular data warehouse

Stream to any popular data warehouse

Load your data into any popular data warehouse, such as Amazon Redshift, Google BigQuery, Snowflake, MemSQL, or MySQL.
Set up in minutes

Set up in minutes

You can set up your data pipeline, from source to data warehouse, in minutes. Export, transform, and consolidate data from any number of silos into any data warehouse.
Work with hundreds of integrations

Work with hundreds of integrations

Alooma also supports a vast array of native integrations across databases, SaaS applications, on-premise and cloud storage, APIs, SDKs, and custom sources.
Use real-time, scheduled, and batch ETL

Use real-time, scheduled, and batch ETL

Transform and enhance your data in motion. Enjoy the flexibility of changes on the fly, whether your ETL is in real time, scheduled, or in batch.
Enjoy high throughput

Enjoy high throughput

Pumping large volumes of data at scale to a data warehouse is difficult. Alooma can reliably handle billions of events per day with super low latency.
Be assured your data is safe

Be assured your data is safe

Alooma is a data-in-motion platform that ensures that every event is secure — in motion or at rest.

Learn more about data warehousing

What is a data warehouse and how does it relate to ETL?

A data warehouse is a large repository of integrated data from one or many disparate sources. Data warehouses can contain historical or current data, typically for analytics and reporting. The data can come from operational systems like Salesforce or Marketo, from application SDKs or APIs, or even sensor data in the case of IoT. This data may require some cleansing, schema changes, or general formatting prior to use.

ETL for extract, transform, load and includes a process by which heterogeneous data is made homogeneous. The transform step typically adjusts data schema and format to work with the target data warehouse, prior to loading it. During this final load step, data is written to the target database or data warehouse.

What are the key characteristics of a data warehouse?

Data warehouses — and the data they contain — typically embody the following four aspects: first, the data in them is subject-oriented — it helps you answer questions on subjects relating to your business. Your data warehouse contains data that was integrated from multiple sources, typically via an ETL tool. Next, a data warehouse is meant to help you analyze changes over time, so your data is time-variant. Finally, your data is nonvolatile — once it has entered your data warehouse, it should not change.

What are some common data warehouse tasks?

At Alooma, we've identified four primary use cases for modern cloud-based data warehouses. Ad-Hoc analysis involves creating business reports from disparate data sources, raw or in aggregate. Machine learning and data science uses statistical algorithms on large datasets to identify trends, discover hidden data relationships, and predict future events. Real-time and operational analytics involves monitoring business and team data by running continuous queries about various key performance indicators (KPIs). Finally, mixed-workload analytics requires some combination of the above use cases across an entire organization.

What are the benefits of a data warehouse?

A data warehouse, especially with a modern ETL pipeline, lets you integrate, access, and analyze all of your data in real time. With these tools, you can gain meaningful insights into your KPIs, create sophisticated business reports, and use advanced machine learning algorithms to predict future events. And you can do it all with unparalleled speed, reliability, security, accuracy, and ease.

Cloud-based or on-premise?

A cloud-based data warehouse is generally more reliable than an on-premise solution. The former may be maintained by the best data warehouse experts around, whereas the latter is only as good as your team. Cloud-based warehouses typically outshine their on-premise counterparts in terms of speed, reliability, security, and ease of use. Rather than continually fighting to reinvent the wheel, your users may immediately gain insights from their data, modernize their processes as new technology is developed, and even develop add-on functionality quickly and incrementally.


More solutions


Get your data flowing today!
Contact us to start using Alooma for free