Appen vs Databricks

By valuation, Databricks is the larger company at $134B versus $341M — a 393x difference. Size can also be measured by team: Appen employs 1000+ people while Databricks has 6,000 employees.

Databricks has raised $20.2B in disclosed funding across 5 known rounds. Appen's funding history is not publicly available.

Databricks leads with an Awaira Score of 93/100, while Appen sits at 55/100. That 38-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Appen was founded by Mark Brayan in 1996. Databricks was founded by Ali Ghodsi in 2013. Visit each company's profile on Awaira for a full founder biography.

Appen: Appen is an AI training data collection and annotation company that provides human-annotated datasets, relevance judgements, and content quality evaluation services used to train and evaluate AI models for search engines, voice assistants, autonomous vehicles, and generative AI systems. The Sydney company operates a global crowd workforce of over one million contractors who perform data annotation, transcription, translation, and content evaluation tasks under managed quality assurance processes.\n\nPublicly listed on the Australian Securities Exchange under ticker APX, Appen has historically generated revenue from long-term data services contracts with major US technology companies including Google, Meta, Amazon, and Microsoft. The company has faced significant revenue pressure as its largest clients have reduced external data annotation spending in favour of internal annotator teams and synthetic data generation, resulting in revenue declines and strategic restructuring since 2022.\n\nAppen competes in the AI data services market against Scale AI, Surge AI, and DataAnnotation, as well as crowdsourcing platforms including Amazon Mechanical Turk. The company faces structural challenges as generative AI and synthetic data approaches reduce demand for the human-annotated data that has historically been its primary product. Appen has been pursuing strategic alternatives including diversification into AI deployment services and government data contracts to offset declining technology company data annotation revenue, reflecting the broader market disruption facing traditional human annotation businesses. Databricks: Databricks is an AI and data platform founded in 2013 that provides a unified analytics workspace for data engineering, data science, and machine learning. The company developed Databricks Lakehouse, which combines data lake and data warehouse capabilities, built on Apache Spark technology. Its platform enables organizations to process large-scale data, build machine learning models, and deploy AI applications through a single interface. The company offers several core products: Databricks SQL for analytics, Databricks Machine Learning for model development, and Databricks Jobs for workflow automation. The platform supports multi-cloud deployment across AWS, Azure, and Google Cloud. Databricks serves enterprises across various industries, with customers including organizations in financial services, technology, and healthcare sectors. As of its latest funding round, Databricks has raised $11.2 billion in total funding and maintains a valuation of $134 billion, positioning it among the highest-valued private AI and data companies. The company achieved Series J funding status, indicating significant capital accumulation and investor confidence. Databricks competes with platforms like Snowflake, Teradata, and cloud-native data solutions from major hyperscalers. The company's growth trajectory reflects strong market demand for integrated data and AI infrastructure, driven by increasing enterprise adoption of machine learning and data-driven decision-making. Databricks unified the traditionally separate data warehouse and data lake approaches through its Lakehouse architecture, creating a single platform for analytics and AI workflows.

Appen got there first, launching in 1996 — that's 17 years of extra runway. Databricks didn't arrive until 2013. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Appen has about 1000+ employees; Databricks has about 6,000. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both Appen and Databricks compete in AI Data, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.