Ocient is a company that enables organizations to explore and interact with hyperscale data sets quickly, cost-effectively, and in previously infeasible ways to deliver meaningful insights and drive customer innovation. Pulse 2.0 interviewed Dylan Murphy, VP of product at Ocient, to learn more.
Dylan Murphy’s Background
Murphy spent over 15 years helping customers solve some of their most complex data analytics challenges. Murphy said:
“When I was with IBM, I supported technical sales of data products on the mainframe and later became the worldwide product manager of IBM’s data replication portfolio. Prior to joining Ocient, I was the CEO of a SaaS startup.”
“I graduated from Pepperdine University with a bachelor’s degree in computer science and business, as well as from the University of British Columbia with a master’s degree in software systems.”
Primary Responsibilities At Ocient
“As VP of product at Ocient, my primary responsibility is to make sure that we’re focused on our customers’ problems. I do this by leading a fantastic team of product managers and documentation experts. I orchestrate their work and synthesize it into a plan that spans all parts of the Ocient solution. Additionally, I work with Ocient executives to make sure that our different organizations are aligned on the roadmap, and collaborate with folks across engineering, marketing, sales, and more to ensure we’re working together to deliver the best possible outcomes for our customers.”
Favorite Memory
What is your favorite memory working at Ocient? Murphy shared:
“Since joining the company in 2019, my favorite memories working at Ocient all have to do with people — our employees and our customers. They’re memories of working with my friends to solve extremely challenging problems. From customer workshops to internal sprints with engineering, arriving at the destination for a customer — like standing up a new production solution — is fantastic. However, the journey is where all my favorite memories occur.”
Challenges Faced
What are some of the challenges Murphy faced in building the company, and has the current macroeconomic climate affected the company? Murphy acknowledged:
“We know that in today’s macroeconomic environment, companies need to balance initiatives geared towards innovation against the need for cost-efficiencies and savings.”
“Ocient is committed to supporting the evolving needs of enterprises by enabling companies with capabilities that allow them to increase price performance and consolidate resource-intensive tools into a single solution so they can unlock opportunities for innovation while still bringing efficiencies and cost savings to their business. Learn more in our recent press release announcing version 22 of the Ocient Hyperscale Data Warehouse.”
Core Products
What are Ocient’s core products? Murphy explained:
Ocient’s flagship product, the Ocient Hyperscale Data Warehouse (OHDW), transforms and loads data in seconds, executes complex queries on hyperscale datasets, and brings AI, machine learning, and geospatial analytics into a single, consolidated solution.
The OHDW supports workloads across real-time analytics, OLAP data warehousing and complex ETL/ELT environments within a single solution, which enables customers to drastically reduce the cost and complexity of hyperscale data management environments while increasing performance and key capabilities.
The OHDW includes these features:
-Native support for traditional ETL workflows, ELT pipelines, and streaming transformation during ingestion.
-Ability to streamline complicated loading processes and eliminate the need for standalone tools like Spark and Informatica that add complexity and overhead to hyperscale workloads.
-Peak performance using clustering, partitioning, compute adjacent storage, compression, and more delivers the performance at scale required to power next-generation data analytics (see more here).
-Query optimization with the Ocient Hyperscale SQL Optimizer
-Leverages machine learning at scale to optimize the execution path for every query and return smarter results faster.
-Supports semi-structured data (see more here).
–Support for geospatial analytics.
-Natively supports more geospatial functions than any other data warehouse provider, enabling organizations to use key geospatial capabilities to power complex, compute-intensive workloads with ease (see more here).
-Machine Learning
-With Ocient, companies can build models without moving data, save time on training with SQL, and leverage hyperscale data volumes for fresher insights (see more here).
Evolution Of Ocient’s Technology
How has Ocient’s technology evolved since launching?
Murphy noted:
“Since exiting stealth mode in 2022 with the general availability of Ocient version 19, The Ocient Hyperscale Data Warehouse has evolved to introduce and include:
Version 20 (press release)
-A new suite of indexes.
-Native complex data types.
-Creation of data pipelines at scale to enable faster and more secure analysis of log and network data for multi-petabyte workloads.
Version 21 (press release)
– Seven new geospatial functions, bringing the total library of Ocient-supported native geospatial functions to more than 120.
-Suite of secondary indexes to access and retrieve data faster than other data warehouses.
-New ML models to enable data scientists to query source data efficiently and directly from the Ocient database.
-Extended OS support for Ubuntu 20.04, Debian 11, and RHEL 8.
-Enhanced system management for graceful node shutdown.
-Browserless SSO for more secure and easier user access control for administrators.
-Workload management dynamic priority.
Version 22 (press release)
– Newly improved performance with the OHDW for loading, streaming, and extract, load, transform (ELT) workloads.
– Hyperloglog (HLL) sketches generally available (GA) for Ocient’s suite of real-time analytics capabilities, including for rollups of data using approximations on aggregated metrics for accelerated query processing.
– New query performance enhancements via I/O pushdown and join optimizations on hyperscale tables with hundreds of billions of rows.
– New integrations with Metabase and Superset for easy data visualization and integration into existing customer environments.
Significant Milestones
What have been some of Ocient’s most significant milestones?
2016: Founded at the request of the world’s largest data-analyzing enterprises.
2018: Ocient raised its Series A funding.
2021: Ocient raised its Series B funding, led by OCA Ventures and Greycroft.
2022: Ocient exited stealth mode with the launch of Ocient version 19. MediaMath selected Ocient for next-gen campaign forecasting. Basis Technologies selected Ocient for hyperscale data analytics. Ocient won the 1871 Momentum Award. Ocient won the 2022 Chicago Innovation Award. General availability of the Ocient Hyperscale Data Warehouse on Google Cloud Marketplace. General availability of the Ocient Hyperscale Data Warehouse on AWS Marketplace. Industry Analyst group ESG wrote about Ocient in a technical review. Featured in a Ventana Research report “Ocient Delivers Ad Hoc Analytics on Hyperscale Workloads.”
2023: Ocient achieved 171% year over year growth. Ocient was recognized by Forrester Research Ocient as a notable vendor in the “The Cloud Data Warehouse Vendors Landscape, Q1 2023” report. Ocient launched version 22 of its OHDW. Dun & Bradstreet re-platformed from a legacy Netezza and mainframe solution to Ocient on Google Cloud
Customer Success Stories
Can you share any specific customer success stories? Murphy highlighted the following:
Ocient and Basis Technologies
Basis Technologies was facing a number of challenges with its existing data warehouse platform, including the inability to scale to support the increasing volume of data being generated, and the lack of performance and latency needed to make real-time decisions.
With Ocient, Basis Technologies was able to:
— Consolidate 10 workloads on a single platform, which reduced the time to query from 24 hours to minutes or less.
— Increase the amount of data stored and analyzed by 10 times, while cutting costs by 30%.
— Improve campaign forecasting accuracy by 10%, which resulted in an increase in ad revenue of 2%.
— Increase audience insights by 20%, which led to a more effective targeting of ads.
A case study and a press release are available for further reading.
Ocient and Dun & Bradstreet
As support for their Netezza environment neared its end, Dun & Bradstreet wanted to re-evaluate their digital strategy with an eye to cost savings and performance improvements.
Additionally, they had to migrate years’ worth of data points to about 500 million commercial entities in their data cloud, with their data volume growing by 10% yearly. Furthermore, the new solution needed to run on the Google Cloud Platform.
After implementing Ocient Hyperscale Data Warehouse, Dun & Bradstreet successfully migrated its critical workloads within two months. In the first four months, the team re-platformed over one million CPU units, delivering a 96.3% reduction overall in elapsed processing time.
A case study is available for further reading.
Use Cases
Ocient is focused on hyperscale use cases in industries, including:
1.) Telecommunications: visibility, operations and IPCR, call detail record (CDR), content delivery network monitoring (CDN).
2.) Adtech: real-time bidding log analysis and historical campaign reporting and attribution.
3.) Government.
4.) Financial services.
5.) Industries that leverage geospatial data at scale.
Differentiation From The Competition
What differentiates Ocient from its competition? Murphy pointed out that Ocient differentiates from its competition in a few key areas:
– Against real-time analytics databases, Ocient delivers: More complete, enterprise-ready features for ETL/loading, indexing, concurrency, and workload management (WLM). Additional features to enable data warehousing/OLAP workloads at scale (e.g., joins, etc.). Data retention and ML capabilities at scale. Flexibility to deploy on-premises/hybrid.
-Against legacy solutions, Ocient delivers: The ability to modernize the data and analytics stack while gaining in performance and lowering costs. Flexibility to keep data on-premises, on the cloud, or a hybrid solution. Modernize legacy infrastructures sitting on Hadoop, mainframes, Vertica, and Teradata to achieve new levels of performance while drastically reducing costs. Enrich SMF/mainframe data with complex, temporospatial data types.
-Against ETL/ELT tools, Ocient can: Replace complex ETL environments, delivering cost savings with the elimination of a third-party tool. Streamline the data and analytics stack to reduce latency and maintenance complexities at hyperscale. Manage data pipelines at scale leveraging standard SQL
Against cloud data warehouses, Ocient provides: Ten to 100 times performance improvements and 50%-80% cost savings at scale (more than 500 core systems, hundreds of terabytes workloads). Compute adjacent storage architecture (CASA), which delivers more efficient I/O with lower latency. Secondary indexing, ML, geospatial, workload management (WLM) capabilities. Elimination of data sprawl via consolidation/scale. Flexibility to deploy on-premises/hybrid for security/control/cost.
Future Company Goals
What are some of Ocient’s future company goals? Murphy concluded:
“We’re focused on continuing to deliver against our organization’s mission and vision as customers’ data challenges grow in size and complexity – especially as data efficiencies with AI continue to be explored in the market.”
Ocient’s vision: a world in which people and enterprises realize significant value in analyzing the data around them without limits on performance, scale, or cost efficiency.
Ocient’s mission: to create, advance, sell and support the leading high-performance data platform the world uses to analyze its hyperscale data sets.
