Qlik unveils a pair of new integrations with Databricks

Qlik has expanded its partnership with Databricks with the launch of two new integrations.

Qlik, founded in 1993 and headquartered in King of Prussia, Pennsylvania, is an analytics and data integration provider whose platform is built around the principle of active intelligence, which Qlik defines as the providing information to customers in real time on any device.

Like its peers including MicroStrategy and SAS, Qlik has shifted its focus from on-premises capabilities to cloud-based analytics. And as part of this evolution, it has adopted a cloud-agnostic strategy that includes partnerships and integrations with data cloud providers, including AWS, Google Cloud Platform (GCP), Microsoft Azure, Snowflake, and Databricks.

Databricks, on the other hand, is a data lakehouse provider founded in 2013 and based in San Francisco. Its Lakehouse platform is a combination of data warehouse and data lake, designed to enable customers to work with structured data using SQL like in a data warehouse and query unstructured data like in a data lake.

New integrations

Databricks Lakehouse (Delta) Endpoint and Qlik Cloud integration with Databricks Partner Connect – both launching on September 26 – represent the latest collaboration between the vendors.

Databricks Lakehouse (Delta) Endpoint is a Qlik Data Integration tool that takes advantage of new Databricks SQL interfaces to allow common users to ingest data with Qlik Data Integration and transport it into Delta Lake on Databricks in real time. A previous integration between Qlik Data Integration and Databricks did not include the SQL-based interfaces.

Meanwhile, Qlik and Databricks also have an integration between Qlik’s analytics tools and Databricks’ Lakehouse that allows joint customers to access and analyze their data already stored in Databricks.

The integration between Databricks Lakehouse and Qlik Data Integration is important to ensure that Qlik customers can leverage their existing investments and skills to integrate data into Databricks Lakehouse.

Matt AslettAnalyst, Ventana Research

It is this ability to use Qlik both before and after storing data in Databricks that makes Qlik integrations, including the Databricks Lakehouse (Delta) Endpoint evolution, significant, according to Matt Aslett, analyst at Ventana Research. .

“The integration between Databricks Lakehouse and Qlik Data Integration is important to ensure that Qlik customers can leverage their existing investments and skills to bring data into Databricks Lakehouse,” he said.

Aslett added that the demand for data lakes is growing and with that growth comes the need for data analytics and integration vendors to ensure that their tools work with those of the data lake vendors and of data lakehouses.

“Data lake environments primarily co-exist with existing investments in data processing and analytics, so it is imperative that data lake environments can be used with both customers’ existing data integration and their analytics products and services,” he said.

The result of the new integration is a more efficient data ingestion process than was available with the previous integration, according to Itamar Ankorion, senior vice president of technology alliances and general manager of enterprise data integration. at Qlik.

According to Donald Farmer, founder and director of TreeHive Strategy.

Additionally, Qlik’s suite of connectors enables the integration of complex data into Databricks so that users can perform analysis on more complete datasets, he continued.

“The Qlik architecture – in particular its wide range of replication and change data capture connectors – allows Databricks Lakehouse to integrate heterogeneous data sources, including legacy sources, which can be very difficult to integrate from another way,” Farmer said. .

An example dashboard from Qlik shows the sales performance of various outlets.

Meanwhile, the integration between Qlik Cloud and Databricks Partner Connect aims to allow Databricks customers to try out Qlik and experience how the platforms work together.

The development of the two new integrations resulted from a combination of Qlik’s desire to take advantage of Databricks’ latest technology – SQL-based interfaces, in the case of Databricks Lakehouse (Delta) Endpoint – and customer feedback, according to Ankorion.

“As Databricks’ product evolved with new features, we invested to align with them to deliver more value to joint customers,” he said. “In addition, customers always prefer and demand cost-performance optimizations.”

Cloud Connectivity Comparison

As more and more customers migrate their data to the cloud, many analytics vendors have made efforts to enable these customers to use the cloud of their choice by developing connectors and integrations with the various clouds of data.

For example, SAS, although its platform is compatible with most major clouds, has developed a close partnership with Microsoft Azure and continues to add features together with Microsoft. Even smaller providers like Toucan Toco are aligning themselves with the various cloud data platforms.

But with data integration, Qlik is among the most advanced in connecting with AWS, Azure, GCP, Databricks, Snowflake and others, according to Farmer.

The vendor’s platform does not offer scenario planning tools. And it could improve its mining, processing and loading capabilities, analysts said. But to connect data integration tools to cloud data warehouses and data lakes, Qlik has come a long way following its acquisition of Attunity in 2019.

Attunity was the first third-party data integration vendor to integrate with Amazon Redshift, dating back to 2013 just after the launch of the tech giant’s cloud data warehouse, Farmer noted.

“So Qlik has more experience with cloud data integration than any other vendor on the market,” he said. “And it shows in the robustness, performance and rigor of their offering.”

Looking ahead, Farmer added that he would like to see more connections between Qlik’s data management and administration tools and cloud service providers.

“Many cloud data platforms are weak in terms of administration and management, and Qlik can fill that gap,” he said.

Ankorion, meanwhile, noted that Qlik is indeed working with the various cloud data platform vendors, including Databricks, to add more integrations, though he didn’t name specific Qlik capabilities. involved in the next wave of these integrations.

About Donnie R. Losey

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