Coralogix vs Weaviate

Weaviate has a disclosed valuation of $200M, while Coralogix's valuation is not publicly available, making a direct size comparison difficult. Weaviate employs 80 people.

Coralogix has raised more in total funding at $270M, compared to Weaviate's $67.5M — a gap of $202.5M. Combined, the two companies have completed 3 known funding rounds.

Weaviate holds the higher Awaira Score at 72/100, compared to Coralogix's 68/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 4-point gap that reflects meaningful differences in scale or traction.

Coralogix was founded by Ariel Assaraf in 2015. Weaviate was founded by Bob van Luijt in 2019. 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. Weaviate: Weaviate is a Netherlands-based vector database company founded in 2019 that enables organizations to build AI applications using vector search and semantic search capabilities. The platform stores, indexes, and searches unstructured data—including text, images, and audio—by converting them into vector embeddings, making it suitable for large language model applications and retrieval-augmented generation (RAG) systems. The core product is an open-source vector database with both community and enterprise versions. Weaviate allows developers to perform similarity searches and build knowledge graphs with semantic understanding. The platform integrates with machine learning frameworks and supports various embedding models, enabling organizations to power AI applications without extensive machine learning infrastructure expertise. Founded during the emergence of modern AI applications, Weaviate operates in the expanding vector database category competing with Pinecone, Milvus, and Qdrant. The company has raised $68 million across funding rounds with a valuation of $200 million as of its Series B stage. Weaviate serves use cases across e-commerce recommendation systems, content discovery, semantic search, and enterprise search applications. The company has gained adoption among developers and organizations building AI-powered products. Its open-source approach provides both community engagement and enterprise monetization pathways. The vector database market has experienced significant growth as organizations increasingly adopt large language models requiring efficient vector storage and retrieval infrastructure. Weaviate combines open-source accessibility with enterprise vector database capabilities positioned to capture growth in RAG and semantic search application development.

Coralogix was founded first in 2015, giving it 4 years of additional market experience. Weaviate was founded later in 2019. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.

Coralogix has approximately 100-500 employees, while Weaviate has approximately 80. A larger team often signals higher revenue or venture backing, but in AI, smaller teams are increasingly capable of building at scale.

Yes, Coralogix and Weaviate are direct competitors — both operate in the AI Data space and likely target overlapping customer segments. This comparison is especially relevant for buyers evaluating both platforms.