Open Lakehouses, End User Simplicity, Open Source Managed Services and SQL Workloads Will Dominate
Ahana’s Cofounder and Chief Executive Officer, Steven Mih and Cofounder and Chief Technology Officer, Dave Simmon predict major developments in cloud, data analytics, open lakehouses and open source in 2023.
Steven Mih, Cofounder and CEO, outlines the major trends he sees on the horizon in 2023:
- End user experience becomes a top priority: As deep integrations of data platforms become standard, the reduced complexity will usher a focus on end user experience. The data platform will become abstracted even further to end users. Instead of worrying about the underlying engines and data structures, end users will be able to easily and seamlessly leverage powerful underlying engines for interactive, batch, real-time, streaming and ML workloads.
- Industry accepted open lakehouse stacks will emerge: As the market further chooses open options for table formats, compute engines and interfaces, the Lakehouse version of the LAMP stack will emerge. Linux Foundation and Apache Software Foundation projects will constitute those components.
- Open source SaaS market will shift toward open source managed services: As data and analytics workloads proliferate in the public cloud accounts, and as IT departments demand more control of their own data and applications, we’ll see the adoption of more cloud native managed services instead of full SaaS solutions.
- Public cloud providers will make huge investments into open source software, and make more contributions back to the community: In the past cloud vendors have been accused of strip-mining OSS software projects. Cloud vendors will go on the “offensive” by contributing to open source more aggressively and even donating their own projects to open source communities.
- SQL workloads will explode as more NLP (Natural Language Processing) and other Machine Learning (ML) applications generate SQL: While data analysts and scientists continue to uncover insights using SQL, increasingly we’ll see apps that “speak SQL” drive a large portion of the analytical compute. Natural Language Processing (NLP) applications both enable citizen data analysts and demand more compute on data platforms. Similarly, ML applications can dig into datasets in new ways which will blow through today’s level of demand for analytic compute. SQL is not only the ‘lingua franca’ of data analysis, SQL is the ‘lingua franca’ of ML and NLP too.
Dave Simmon, Co-founder and CTO, outlines a major trend he sees on the horizon in 2023:
- Open lakehouse will more effectively augment the proprietary cloud enterprise data warehouse: As the architectural paradigm shift toward the lakehouse continues forward, the disaggregated stack will become more fully-featured data management systems from disjointed components evolving into cohesive stacks that include metadata, security and transactions.
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