Alooma
The Modern Data Pipeline

In the world of big data, the increasingly common task of pipelining data from disparate data sources into an Online Analytical Processing (OLAP)-friendly medium can be cumbersome, especially when there are multiple data sources. Further, as new technological requirements are added, greater scalability becomes necessary for organizations to manage data pipelining. To this end, it might be best to use a hosted service to handle the plumbing so that organizations can focus on areas that matter the most for their business. Enter Alooma. Through its all-inclusive platform, the company can collate data from various data silos together to an organization's data warehouse in real time, creating data visibility and control for their data teams. We got into a conversation with Yair Weinberger, the CTO and co-founder of Alooma to learn how the company's Data Pipeline as a Service platform provides data scientists and engineers with the ability to integrate, clean, and enrich data from various data silos at any time, to any destination.

Alooma was established in 2013. What has changed in the last five years?

There have been three major changes in this period. When we came in, the cloud was very common, however, the bigger enterprises were fully on-premise. They were afraid to give the control of their data to an external service provider. There has been massive growth in the trust factor of cloud as cloud migration has become the focal point for many large players. Secondly, there has been a second wave of cloud service providers, and lastly security and compliance has emerged to be a major concern especially for the government sector. The burden of complying with regulations has been a challenge for the CIOs.

We are spearheading these changes by collaborating with different companies such as Amazon, Google, Microsoft, and Snowflake. We have transformed from supporting companies that are 'born in the cloud' to large enterprises which have only been using on-premise storage and are migrating to the cloud. By supporting enterprise-grade data sources and security requirements, we not only stream data but also ensure that every event is securely transferred to the data warehouse. Alooma leverages multiple layers of defense to ensure all data is protected from unauthorized access and tampering. The Alooma service runs inside a Virtual Private Cloud, with individual hosts protected by firewalls configured with the most stringent rules. All communication with the Alooma service is protected at the network level using industrial-strength, secure protocols. A secured architecture, internal best practices, third-party certifications and audits are all important components of our security program. We are SOC 2 Type II, GDPR, and HIPAA compliant.

How does Alooma’s platform provide visibility and control to the clients?

The Alooma platform connects to multiple data sources (and types of data sources) such as Cassandra, MongoDB, MySQL, Salesforce, and many others without a lot of fuss, transforming and cleaning all the data very quickly. Alooma's Code Engine supports Python transforms of the data along the way. The data is then loaded into a data warehouse. If any data fails to load for whatever reason, it is captured via the Restream Queue to be reloaded later. The idea is to execute data processing with data streaming in real time delivered as a cloud service that can scale to meet whatever data requirements the customer has.

The platform provides the ability to collate data from different silos and enrich it according to the clients' needs. Alooma takes the busywork out of data discovery, mapping, and transformation to make data migration easier than ever. Further, Alooma infers schemas and allows clients to automatically map their integrations with OneClick mapping, or take charge with custom mappings where they want ultimate control.

Is there a specific case study example that you can provide us where Alooma assisted the client in mitigating specific challenges?

With advanced business intelligence requirements in mind, Quid’s main priority was to automate data collection from disparate data sources, without requiring significant engineering resources. All of the tools that they use have data. And thus being able to connect all that data in a way to understand what’s working and what’s not is critical to the growth of their business.

Alooma provided the flexibility that Quid needed: just the right balance between being able to automate changes with the click of a button, yet working with embedded Python code to easily transform the data as much as we need on the fly. All without requiring any engineering resources to build the data collection infrastructure. Alooma made Quid’s 'dream business intelligence' infrastructure a reality, enabling the company to make crucial business decisions-all while saving the Quid team development time and significant engineering costs.

What does the future look like for Alooma?

For the short term, we will expand and try to acquire more customers. On the long term, we will be following our core goal of enabling businesses to use all of their data to make better data-driven decisions. We are headquartered in Redwood City, CA, and are funded by leading venture investors, including Sequoia Capital and Lightspeed. Going ahead, we will be building a unique niche for us in the cloud services sector, which is very populated right now.