Coralogix vs Databricks

By valuation, Databricks is the larger company at $134B versus $1B — a 134x difference. Size can also be measured by team: Coralogix employs 100-500 people while Databricks has 6,000 employees.

Databricks has raised more in total funding at $20.2B, compared to Coralogix's $350M — a gap of $19.9B. Combined, the two companies have completed 11 known funding rounds.

Databricks leads with an Awaira Score of 93/100, while Coralogix sits at 68/100. That 25-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Coralogix was founded by Ariel Assaraf in 2015. Databricks was founded by Ali Ghodsi in 2013. Visit each company's profile on Awaira for a full founder biography.

Coralogix: Coralogix provides a machine learning-powered log analytics and observability platform that uses AI to reduce the volume of logs requiring full indexing and storage, applying streaming ML analysis to detect patterns, anomalies, and insights in log data without requiring all data to be indexed at query time. The Tel Aviv and San Francisco company stateful streaming approach reduces observability costs significantly compared to traditional log management tools that index and store all data regardless of utility.\n\nThe company raised approximately $270 000 000 including a Series D round from investors including Brighton Park Capital, Greenfield Partners, and Telstra Ventures. Coralogix counts technology companies and enterprises across cloud-native software development, fintech, and SaaS as clients, competing on cost efficiency relative to Datadog, Splunk, and New Relic for engineering teams with high log ingestion volumes and constrained observability budgets.\n\nCoralogix competes in the log management and observability market where Datadog, Elastic, and Grafana hold dominant positions. Its cost optimization positioning resonates with engineering teams managing rapid data growth who face steeply rising observability bills from usage-based pricing models at incumbent vendors. The company TCO reduction messaging is backed by architectural decisions that trade query flexibility at indexing time for streaming ML analysis that surfaces issues without storing all log data, a trade-off that appeals to cost-conscious engineering operations teams at high-growth software companies. 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.

Databricks got there first, launching in 2013 — that's 2 years of extra runway. Coralogix didn't arrive until 2015. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Coralogix has about 100-500 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 Coralogix and Databricks compete in AI Data, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.