Welcome to the Molecula 2.0 Enterprise Feature Store
Access big data at unprecedented speeds with no compromise
Today, we’re excited to announce the release of Molecula 2.0!
Since May of 2019, when we debuted our groundbreaking technology, we have validated the importance of helping enterprises simplify, accelerate, and control data access. Molecula is working with Global 2000 organizations to simplify big data infrastructure and exponentially accelerate queries starting at 1000x. While 1000x acceleration is an astonishing technical feat, it’s the business results that truly matter.
Today, Molecula’s unique ability to deliver highly-performance representations of large, disparate data sources eliminates the need to pre-aggregate or federate, reducing data-delivery cycles and data gravity. Customers and Partners like Q2 and Power Analytics rely on Molecula to help achieve a data-driven enterprise by accelerating decision making and analyzing large, distributed data sets across any cloud, core and edge.
“We are very excited to leverage Molecula’s Cloud Data Access platform to speed up our data processing workflows and gain much deeper insights on our customers and product usage. Molecula helps us access the hardest and the largest datasets at extreme performance – in real-time – and in a way that seamlessly integrates into our existing big data environment.”
–Kevin Meagher, President | Power Analytics
Needless to say, the market response to Molecula has been inspiring. We’re fully committed to relentlessly improving the platform’s usability and performance, and we’re exceedingly grateful for all the thoughtful and creative contributions from Pilosa, our open-source community, and our customers who have helped guide our work.
If you are new to Molecula, here’s a good breakdown of the solution our customers have been using for the past year:
What’s New in Molecula 2.0
Molecula 2.0 is not just a version update. It’s a quantum leap over prior versions. This was only possible because of our continued focus on three core areas of customer need: simplifying big data infrastructure, accelerating time from data to decisions, and enhancing the enterprise-native experience.
Starting today, customers now have access to the following capabilities.
Simplifying Big Data Infrastructure with No Compromise
The data access landscape today is far too complex and noisy and the effort involved in making data accessible is far exceeding the value we create with the data. We are determined to radically simplify the way enterprises access big data, and that theme is a constant throughout our business.
In Molecula 2.0 we’ve further simplified accessing and sharing Molecula VDSs:
- VDS Portability: Molecula’s Cloud Data Access platform enables users to move or export VDSs to alternate locations, whether that is another data center, a different cloud, or into cold storage. Our customers have expressed the desire to take advantage of elastic compute for use cases like advanced analytics, BI or machine-learning statistics, that are not ideal for they don’t have access to on-prem environments. The ability to move and persist VDSs up to 100x smaller than the original data footprint to any cloud (private, public or managed), instead of moving the raw datasets, reduces infrastructure and data movement up to costs by at least 10x.
Accelerating Time from Data to Decisions
As we’ve worked with our customers to identify more opportunities to optimize their data-delivery environments, they have consistently shared that pre-aggregation and pre-processing techniques used to integrate datasets from disparate systems can take 4-6 weeks to provision.
This results in long-running queries – from minutes to hours to days, in some cases. Delivering the analytical data lakes, cubes, and data marts needed to serve a single analytical or machine-learning use case can cost upwards of $2M – $3M in production infrastructure.
Now, Molecula users who have virtualized their data can eliminate arduous, expensive and slow integration processes by taking advantage of the platform’s ability to join across disparate datasets and formats at query time. The result is simpler, accelerated, and more secure data access.
With Molecula 2.0 enterprises can execute:
- Low Latency JOINs: Joining data across Virtual Data Sources (VDSs) that represent disparate datasets from multiple underlying source systems. These low latency JOINs query VDS representations of massive datasets eliminating the need to pre-aggregate, federate, copy, cache, or move the original data. For consumption of data, the end users still interact with their preferred tooling, but instead of waiting days or weeks for new data to be delivered in a cube or mart, they are able to query across the data they have access to in an ad hoc fashion in real-time.
Our team works relentlessly to make Molecula feel like, and integrate with, existing enterprise tools, while enabling the ability to take advantage of novel, high performance approaches under the hood.
Molecula 2.0 brings Enterprises:
- Analytical SQL Support: Introducing support for the most commonly used analytical SQL queries such as (but not limited to) aggregations with group by; function on integers; having with group by and aggregate functions; inner joins. The 2.0 Release includes a SQL interface based on the PostgreSQL wire protocol for seamless connectivity.
- Plugins: We have gone to great lengths to build out an extension framework for Molecula to allow seamless integration the most commonly used source systems, formats, and end-user tooling including but not limited to: Kafka, Kafka Connect, S3, MySQL, SQLServer, Teradata, Oracle DB, Cassandra, Spark, Parquet, Snowflake GoldenGate, Tableau, PowerBI, Jupyter, Pandas, Rapids.ai, and more.
What this Means for Customers
This new version of the Molecula platform enables our customers to get even more from their big data at higher speeds than ever before. Our company’s mission is to unlock human potential through the power of data, and Molecula 2.0 delivers on that promise.
To stay up to date on all of our news, follow our blog at www.molecula.com/blog
Molecula’s enterprise feature store simplifies, accelerates, and improves control over big data infrastructure for Advanced Analytics, Machine Learning, and Edge/IoT. Its unique ability to deliver highly-performant representations of large, disparate data sources eliminates the need to pre-aggregate or federate, thus reducing data delivery cycles and data gravity.
Global 2000 organizations rely on Molecula to help achieve a data-driven enterprise by accelerating decision-making, enabling real-time customer segmentation, and analyzing large, distributed datasets across any cloud, from core or edge. Molecula is based on Pilosa, an open-source project with 2,000+ users across many tier-one organizations.
Molecula has offices in Austin and Palo Alto and was founded in 2017 with a mission to unlock human potential through the power of data.
To learn more about Molecula:
Sign up for the 2.0 webinar here
Visit our website www.molecula.com
Learn about our Partnership with Power Analytics here