Build scalable pipelines in minutes that deliver data to power real-time analytics and action: Equalum

Equalum is relied upon by Fortune 500 companies across key industries to stream data in real-time across cloud, on-prem and hybrid environments, powering data warehouse modernization, real-time analytics, AI/BI, and more. Backed by industry-leading change data capture (CDC), Equalum’s platform features drag-and-drop UI, and powerful data replication and ETL tools (including Spark and Kafka) that allow you to build real-time data pipelines in minutes. Equalum was founded in 2015 by Nir Livneh, former Senior Big Data Architect at the IDF and Erez Alsheich, CPO, 20 year veteran data architect, entrepreneur and engineer. Through their years of industry experience, they saw similar obstacles facing data teams as they sought to modernize their data warehouse and environment and move away from legacy systems: technical gaps, coding gaps, tool sprawl, and more. They recognized that many of the issues boiled down to a technical challenge – a solvable one at that – and Equalum was born.

Now serving industry leaders, enterprises, and mid-enterprise companies around the world, Equalum continues its exponential rise as an award-winning data integration & real-time data streaming company to watch.

Change Data Capture (CDC)

The push towards real time data and streaming-first architectures has never been more pervasive than in our current big data and analytics landscape. The volume and velocity of data is ever increasing, causing strain on legacy architectures as they attempt to process it effectively. The complications of ingesting data from operational sources in near real time, transformed and optimized do not come without complexity. Change Data Capture is a low overhead and low latency method of extracting data, compared to traditional batch processes, limiting intrusion into the source and continuously ingesting and replicating data by tracking changes to the data. When designed and implemented effectively, CDC is the most efficient method to meet today’s scalability, efficiency, real-time and low overhead requirements. It is imperative that your business has the right architecture in place to handle high throughput of data, a simplicity of replicating subsets of data and ever changing schema, as well as the capacity to capture the data and the changes exactly once, then replicate or ETL the CDC data to your data warehouse or data lakes, for analytics purposes.

Traditionally, however, organizations were forced to use different ingestion products for each use case, due to the fact that many legacy CDC Replication tools do not have real-time transformation, data manipulation, aggregation and correlation capabilities within the pipe. Alternatively, CDC Streaming Ingestion tools were not built to natively support CDC Replication use cases and are missing key capabilities for this use case. With the addition of the Batch ETL use case, which every organization also uses in some capacity, organizations often find themselves with three different tools to achieve a full implementation of their data ingestion strategy. Using three different tools to support all three use cases is not only extremely cost inefficient, but also leaves the organization with management and maintenance of three tools, different processes, different skill sets and no sense of single point of ownership for their data ingestion approach. It is vital to use the right tool for the right job, but it’s also key to consolidate ingestion processes where possible. Centralize system monitoring. Lower costs on various platform licenses. Streamline your architecture for more transparency into data processing, scalability and ease of use.

Simplify the streams of data

Develop and operationalize your batch and streaming pipelines with infinite scalability and speed. Traditional Change Data Capture and ETL processes and tools cannot adequately perform under the pressure of modern data volumes and velocities. The strain on legacy data systems leads to data latency, broken pipelines, and stale data used for business analytics and daily operations. Equalum built the industry’s most scalable and comprehensive data ingestion platform, combining streaming Change Data Capture with modern data transformation capabilities. While real-time ingestion and integration are core strength of the platform, Equalum also supports high scale batch processing. Equalum supports both structured and semi-structured data formats, and can run on-premises, in public clouds or in hybrid environments. Equalum’s library of optimized and developed CDC connectors is one of the largest in the world, and more are developed and rolled out on a continuous basis, largely based on customer demand. Equalum’s multi-modal approach to data ingestion can power a multitude of use cases including CDC Data Replication, CDC ETL ingestion, batch ingestion and more.

Equalum also leverages open source data frameworks by orchestrating Apache Spark, Kafka and others under the hood. The platform’s easy to use, drag and drop UI eliminates IT productivity bottlenecks with rapid deployment and simple data pipeline setup. The platform’s comprehensive data monitoring eliminates the need for endless DIY patch fixes to broken pipelines and challenging open source frameworks management, empowering the user with immediate system diagnostics, solution options and visibility into data integrity. Headquartered in Silicon Valley and Tel Aviv, Equalum is proud to work with some of the world’s top industrial, financial, and media enterprises globally.

Meet the leader behind the success of Equalum

Guy Eilon, CEO of Equalum is a seasoned Executive with proven success driving expansion and market share for companies across the globe. He brings extensive experience in tackling new, diverse and emerging markets, building highly performant direct and partner sales teams, developing strategic greenfield opportunities and in fostering communities of excellence across geographically dispersed regions.