Reflecting on 2024: ApertureData's Journey and What's Next for Multimodal AI Data Management in 2025.

December 23, 2024
3 Min
No items found.

Happy holidays and wish you an exciting new year as we come out of which LLM is the best and jump into the world of AI Agents, guardrails, and multimodality in 2025!


As we come out of which LLM is the best and jump into the world of AI Agents, guardrails, and multimodality in 2025, we want to thank you for sharing how you are leveraging these exciting developments to enhance customer experience and improve efficiency within your organization. We are especially grateful for the opportunity to explore how we can partner with you in the coming year to help you achieve these goals.

As we reflect on all we have achieved at ApertureData this year, we are extremely proud of our team and very thankful to our current as well as potential customers, investors, and families in supporting this roller coaster of a year!

Some highlights from our journey this year

What ApertureDB can do for you: Multimodal data management for AI is hard but necessary to take you to the next level in this new AI/ML world. ApertureDB makes it very simple. It is the only database that seamlessly combines the capabilities of a memory-optimized graph database with scalable vector database and multimodal dataset management. You only have to work with one database via its unified API. We certainly poured a lot of love in our documentation this year to answer all your questions —including a chatbot powered by ApertureDB vector search!

Scale & Performance: Not only were we able to scale ApertureDB to 1M queries per second, measure some of the best vector search performance in the market (13000+ embeddings per second and sub 10 msec latency), we can also scale to where other popular vector databases fall short! We were able to ingest multimodal datasets with one dataset getting ingested at over 800 images per second. Stay tuned for our benchmarking report in the new year.


Stats on your data: Based on visibility into a small subset of user instances, ApertureDB has been easily managing over 80M objects, 138M connections, 20M images, 52M embeddings, 160K videos, in production. For one of our key customers, ApertureDB has been easily delivering over 8000 embeddings per second with queries coming from over 300 stores! These metrics are continually evolving and our internal tests have proven ApertureDB with billions of objects.

Ease of access: We are committed to making it easy for you to build PoCs and confidently scale to production. In addition to supporting VPC deployments, we've expanded our offerings with ApertureDB in the Cloud, the ApertureDB Community Edition, GCP Marketplace, and DB-as-a-Service on both GCP and AWS. We have got you covered every step of the way!"


Integrations and partnerships: Databases live in an ecosystem of tools and the AI landscape is currently brimming with those! Thank you for sharing which ones you cared about the most because of which, we added connectors and integrations to LabelStudio, LangChain, LlamaIndex (user-contributed!) in addition to PyTorch, Tensowflow, and Vertex AI. We set up ETL pipelines to generate embeddings and metadata from Twelve Labs, OpenAI, Cohere, FaceNet, and other user-provided options. We launched partnerships with GCP and HPE with AWS now on the horizon.

Content: We are always looking to solve as many data challenges as we can for as many users as we can. That requires awareness in the right communities. We launched our newsletter covering real world challenges in multimodal AI, and started connecting with various users during meetups, conferences, and through blogs (our
resource library
).


What to expect from ApertureData in 2025?

We are excited to build on the momentum we have gained in 2024 and continue working together with you to tackle the growing and dynamic challenges of managing text and multimodal data for AI.  Together, we will keep pushing the boundaries and finding solutions that drive real impact!"


A few new efforts that I am very excited about:

  • We will be opening up our collection of application examples, our internal datasets to help you build new applications faster.
  • Our Cloud product is getting some very cool enhancements that you will hear about soon.
  • We will be launching a new lunch & learn series and would love to feature some of our work together.
  • We have lined up more exciting partnerships particularly to help ETL complex data types, extend to agentic workflows, and some very interesting new content.
  • A detailed comparison with various databases.

If you would like to evaluate ApertureDB on your own, please go ahead and try our Quick Start guide. In all cases, I would love to schedule a quick follow up with you and the relevant team to dive deeper into your high priority data use cases in the new year!

Tags:
No items found.

Related Blogs

What’s in Your Visual Dataset?
Blogs
What’s in Your Visual Dataset?
CV/ML users need to find, analyze, pre-process as needed; and to visualize their images and videos along with any metadata easily...
Read More
Watch Now
Product
How do you find what’s in your image or video datasets?
Videos & Podcasts
How do you find what’s in your image or video datasets?
See how ApertureDB Web Frontend simplifies navigating large collections of visual data...
Read More
Watch Now
Product
Find Matching Faces: Metadata and Vector Search in ApertureDB
Videos & Podcasts
Find Matching Faces: Metadata and Vector Search in ApertureDB
See how to search for faces based on metadata constraints and facial similiarity matching...
Read More
Watch Now
Product
Can A RAG Chatbot Really Improve Content?
Blogs
Can A RAG Chatbot Really Improve Content?
We asked our chatbot questions like "Can ApertureDB store pdfs?" and the answer it gave..
Read More
Watch Now
Applied
Building Real World RAG-based Applications with ApertureDB
Blogs
Building Real World RAG-based Applications with ApertureDB
Combining different AI technologies, such as LLMs, embedding models, and a database like ApertureDB that is purpose-built for multimodal AI, can significantly enhance the ability to retrieve and generate relevant content.
Read More
Managing Visual Data for Machine Learning and Data Science. Painlessly.
Blogs
Managing Visual Data for Machine Learning and Data Science. Painlessly.
Visual data or image/video data is growing fast. ApertureDB is a unique database...
Read More
What’s in Your Visual Dataset?
Blogs
What’s in Your Visual Dataset?
CV/ML users need to find, analyze, pre-process as needed; and to visualize their images and videos along with any metadata easily...
Read More
Transforming Retail and Ecommerce with Multimodal AI
Blogs
Transforming Retail and Ecommerce with Multimodal AI
Multimodal AI can boost retail sales by enabling better user experience at lower cost but needs the right infrastructure...
Read More
Vector Databases and Beyond for Multimodal AI: A Beginner's Guide Part 1
Blogs
Vector Databases and Beyond for Multimodal AI: A Beginner's Guide Part 1
Multimodal AI, vector databases, large language models (LLMs)...
Read More
How a Purpose-Built Database for Multimodal AI Can Save You Time and Money
Blogs
How a Purpose-Built Database for Multimodal AI Can Save You Time and Money
With extensive data systems needed for modern applications, costs...
Read More
Minute-Made Data Preparation with ApertureDB
Blogs
Minute-Made Data Preparation with ApertureDB
Working with visual data (images, videos) and its metadata is no picnic...
Read More
Why Do We Need A Purpose-Built Database For Multimodal Data?
Blogs
Why Do We Need A Purpose-Built Database For Multimodal Data?
Recently, data engineering and management has grown difficult for companies building modern applications...
Read More
Building a Specialized Database for Analytics on Images and Videos
Blogs
Building a Specialized Database for Analytics on Images and Videos
ApertureDB is a database for visual data such as images, videos, embeddings and associated metadata like annotations, purpose-built for...
Read More
Vector Databases and Beyond for Multimodal AI: A Beginner's Guide Part 2
Blogs
Vector Databases and Beyond for Multimodal AI: A Beginner's Guide Part 2
Multimodal AI, vector databases, large language models (LLMs)...
Read More
Challenges and Triumphs: Multimodal AI in Life Sciences
Blogs
Challenges and Triumphs: Multimodal AI in Life Sciences
AI presents a new and unparalleled transformational opportunity for the life sciences sector...
Read More
Your Multimodal Data Is Constantly Evolving - How Bad Can It Get?
Blogs
Your Multimodal Data Is Constantly Evolving - How Bad Can It Get?
The data landscape has dramatically changed in the last two decades...
Read More
Can A RAG Chatbot Really Improve Content?
Blogs
Can A RAG Chatbot Really Improve Content?
We asked our chatbot questions like "Can ApertureDB store pdfs?" and the answer it gave..
Read More
ApertureDB Now Available on DockerHub
Blogs
ApertureDB Now Available on DockerHub
Getting started with ApertureDB has never been easier or safer...
Read More
Are Vector Databases Enough for Visual Data Use Cases?
Blogs
Are Vector Databases Enough for Visual Data Use Cases?
ApertureDB vector search and classification functionality is offered as part of our unified API defined to...
Read More
Accelerate Industrial and Visual Inspection with Multimodal AI
Blogs
Accelerate Industrial and Visual Inspection with Multimodal AI
From worker safety to detecting product defects to overall quality control, industrial and visual inspection plays a crucial role...
Read More
ApertureDB 2.0: Redefining Visual Data Management for AI
Blogs
ApertureDB 2.0: Redefining Visual Data Management for AI
A key to solving Visual AI challenges is to bring together the key learnings of...
Read More
Stay Connected:
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.