Open source vector database startup Qdrant raises $28M


The open-source vector database startup Qdrant has raised $28 million in a Series A fundraising round headed by Spark Capital.
Qdrant, the pioneering open-source vector database startup, secures a game-changing $28M in funding!
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The open-source vector database startup Qdrant has raised $28 million in a Series A fundraising round headed by Spark Capital.

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(Image Source: https://finance.yahoo.com/)

The Berlin-based company Qdrant was founded in 2021 and aims to capitalize on the rapidly developing AI industry by providing developers with an open-source vector search engine and database. This is important because generative AI requires the creation of relationships between unstructured data, which includes text, images, and audio that aren’t labeled or otherwise organized, even when the data is “dynamic” and used in real-time applications. According to research from Gartner, unstructured data is expanding three times faster than structured data and accounts for over 90% of all new enterprise data.

The world of vector databases is booming. Weaviate, for example, has raised $50 million for its open-source vector database in recent months, while Zilliz has raised $60 million to market the Milvus open-source vector database. In another instance, Pinecone obtained $100 million for a proprietary alternative, while Chroma obtained $18 million in venture funding for a project akin to this one.

In April of last year, Qdrant, for example, raised $7.5 million, indicating both a projected expansion by Qdrant and the seemingly endless demand for vector databases among investors.

Binary Logic

Nine months have passed since Qdrant’s last funding round. During that time, the company introduced binary quantization (BQ), a new, highly effective compression technology aimed at low-latency, high-throughput indexing that can, according to the company, cut memory usage by up to 32 times and increase retrieval speeds by about 40 times.

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However, it’s up to the user to determine which compression method would work best for their use cases; BQ might only work for some AI models. According to Zayarni, they discovered that OpenAI’s models produced the most outstanding results; however, Cohere and Google’s Gemini also performed well. Currently, Mistral and Stability AI models are being benchmarked against by the company.

These initiatives have drawn prominent adopters, including Accenture, Deloitte, and X (formerly Twitter), which is likely the most well-known. Or, more precisely, Elon Musk’s xAI, a business creating Grok, a ChatGPT rival that debuted its X platform last month.

Because of a non-disclosure agreement (NDA), Zayarni could not discuss specifics about how X or xAI was using Qdrant; however, it is plausible to conclude that Qdrant was being used to process real-time data. Grok leverages a generative AI model called Grok-1 that was trained on web data and human feedback. Because of its (current) close alignment with X, Grok can incorporate real-time data from social media posts into its responses; this is known as retrieval augmented generation (RAG), and over the past few months, Elon Musk has publicly hinted at use cases for this technology.

Quadrant does not disclose which of its clients are using its managed services and which are using the open-source version of the product. However, it did identify several startups that are “mostly” utilizing its managed cloud service, including GitBook, VoiceFlow, and Dust. This relieves resource-constrained businesses of managing and deploying everything independently, as they would have to do with the core open-source incarnation.

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Even if a business chooses to pay for additional services, Zayarni is sure that one of the main selling elements is the company’s open-source credentials.

“There is always a risk of vendor lock-in when using a proprietary or cloud-only solution,” Zayarni stated. Customers must consent to price adjustments or other changes made by the vendor, or they will have to think about switching to a different solution, which will be difficult in the case of a heavy-production use case. You have constant control over your data while using open source and may choose from various deployment choices.

In addition to announcing the fundraising today, Qdrant is formally launching its managed “on-premise” edition, allowing businesses to host everything in-house while still utilizing Qdrant’s premium features and support. This comes after it was announced last week that Qdrand’s cloud edition would be available on Microsoft Azure in addition to the platforms already supported by AWS and Google Cloud.

Unusual Ventures and 42cap participated in Qdrant’s Series A financing in addition to lead investor Spark Capital.

(Information Source: Techcrunch.com)


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