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TerminusDB VS Activeloop

Compare TerminusDB VS Activeloop and see what are their differences

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Contents:
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TerminusDB logo TerminusDB

TerminusDB is an open source model driven graph database for knowledge graph representation designed specifically for the web-age.

Activeloop logo Activeloop

Data lake for machine and deep learning. The fastest dataset management tool for computer vision.
  • TerminusDB Landing page
    Landing page //
    2023-07-28
  • Activeloop Landing page
    Landing page //
    2021-09-20

About

Activeloop provides an optimized format for unstructured data, so users can stream their machine learning datasets while training ML models in PyTorch and TensorFlow. Activeloop acts as a data lake for deep learning on unstructured data and offers in-browser dataset visualization, querying, and version control. On top of those features, Activeloop integrates with experimentation and labeling tools to allow rapid iteration on computer vision datasets.

Activeloop supports the following use cases:

Machine Learning teams can apply Activeloop's data infrastructure to ship their models fast in the following use cases:

  1. AgriTech
  2. Audio processing
  3. Autonomous Vehicles & Robotics
  4. Biomedical and Healthcare ML
  5. Multimedia: Image enhancement, video enhancement, face detection, sports analytics, or machine learning for AR/VR
  6. Safety & Security: surveillance machine learning with biometrics, facial recognition, or crowd counting

TerminusDB

Website
terminusdb.com
Pricing URL
Official TerminusDB Pricing
$ Details
Platforms
-
Release Date
-
Edit details

Activeloop

Website
activeloop.ai
Pricing URL
Official Activeloop Pricing
$ Details
$450 / Monthly (Growth Plan for up to 10 users)
Platforms
AWS GCP Python
Release Date
2019 July
Edit details

TerminusDB features and specs

  • Version Control
    TerminusDB has built-in version control for data, enabling users to manage changes over time, rollback to previous versions, and track data lineage.
  • Collaboration Features
    It supports collaborative workflows with branching, merging, and diffing, making it easier for teams to work together on data projects.
  • Schema Enforcement
    Provides strong schema enforcement to ensure data consistency and integrity, promoting better data management practices.
  • Graph Database Foundation
    Built on a powerful graph database architecture, which offers high flexibility and efficiency for managing complex and interconnected data.
  • Open Source
    TerminusDB is open source, providing transparency and the ability for users to contribute to its development or customize it for their needs.

Possible disadvantages of TerminusDB

  • Learning Curve
    The tool can have a steep learning curve for those unfamiliar with versioned data systems or graph databases, requiring time to master.
  • Limited Community Support
    While growing, the community around TerminusDB is not as large as more established database solutions, potentially limiting peer support and resources.
  • Early-Stage Features
    Some features may still be in early development stages, which might lead to fewer functionalities compared to mature database systems.
  • Performance Overheads
    Version control and schema enforcement can introduce performance overheads, particularly for large datasets or highly dynamic use cases.

Activeloop features and specs

No features have been listed yet.

Analysis of Activeloop

Overall verdict

  • Activeloop is a solid choice for teams working with large-scale AI/ML datasets, particularly those involving unstructured data like images, video, and audio, offering a specialized data infrastructure (Deep Lake) that streamlines dataset versioning, storage, and streaming for machine learning workflows.

Why this product is good

  • Deep Lake format enables efficient storage and streaming of large unstructured datasets directly to ML training pipelines without full downloads
  • Built-in version control for datasets, similar to Git, making it easier to track changes and collaborate on data
  • Native integrations with popular ML frameworks like PyTorch and TensorFlow, plus support for vector search and LLM-based applications
  • Cloud-agnostic storage options allowing flexibility across AWS, GCP, and other providers
  • Strong focus on performance optimization for data loading, reducing bottlenecks in training large models
  • Growing ecosystem with support for multimodal data types, useful for computer vision and generative AI projects

Recommended for

  • ML engineers and data scientists working with large-scale image, video, or audio datasets
  • Teams building computer vision or multimodal AI applications
  • Organizations needing dataset version control integrated into their ML pipeline
  • Developers building retrieval-augmented generation (RAG) or LLM applications requiring vector storage
  • Startups and enterprises looking to optimize data loading performance for deep learning training
  • Teams seeking an alternative to traditional data lakes for AI-specific workloads

TerminusDB videos

+ Add

Welcome to TerminusDB & TerminusHub

More videos:

  • Review - MongoDB vs TerminusDB - TerminusDB Discussion #13

Activeloop videos

+ Add

Activeloop Product Demo Video

Category Popularity

0-100% (relative to TerminusDB and Activeloop)

TerminusDB

Activeloop

Graph Databases
100 100%
Graph Databases
0% 0
Machine Learning
0 0%
Machine Learning
100% 100
Databases
100 100%
Databases
0% 0
Data Science
0 0%
Data Science
100% 100

User comments

Share your experience with using TerminusDB and Activeloop. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, TerminusDB should be more popular than Activeloop. It has been mentiond 16 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

TerminusDB mentions (16)

  • Show HN: Graphiti – LLM-Powered Temporal Knowledge Graphs
    Have you seen TerminusDB? [0] They’ve got a nice solution to versioned RDF graphs, originally pitched as “Git for data” but focused on knowledge graphs. I’m not affiliated (in fact they launched around the same time that my co-founder and I launched Splitgraph with the same “Git for data” pitch), but I find their technology very intriguing. Knowledge graphs are on the cusp of revival after being in stasis for 20... - Source: Hacker News / almost 2 years ago
  • Help with some python DB client installation errors please
    Hey, I'm trying to install TerminusDB. They have the python client installation instructions here. Source: almost 4 years ago
  • Is there a terminusdb package?
    Hi, I wanted to check if there's a NixOS package for TerminusDB. Source: almost 4 years ago
  • free-for.dev
    TerminusX — Managed free service for TerminusDB, a document and graph database written in Prolog and Rust. Free for dev, paid service for enterprise deployments and support. - Source: dev.to / almost 4 years ago
  • My ultimate/dream language -- tldr; LP/FP typed prolog
    As someone interested in prolog (and co-founder of terminusdb.com) I can sympathise a lot with your laundry list there :D Lack of type and mode annotations is a hassle on small programmes, and a serious problem on large ones just from the point of view of avoiding bugs, without even getting into performance. Source: almost 4 years ago
View more

Activeloop mentions (4)

  • [P] I built a Chatbot to talk with any Github Repo. 🪄
    This repository contains two Python scripts that demonstrate how to create a chatbot using Streamlit, OpenAI GPT-3.5-turbo, and Activeloop's Deep Lake. The chatbot searches a dataset stored in Deep Lake to find relevant information and generates responses based on the user's input. Source: over 3 years ago
  • [D] NLP has HuggingFace, what does Computer Vision have?
    u/Remote_Cancel_7977 we just launched 100+ computer vision datasets via Activeloop Hub yesterday on r/ML (#1 post for the day!). Note: we do not intend to compete with HuggingFace (we're building the database for AI). Accessing computer vision datasets via Hub is much faster than via HuggingFace though, according to some third-party benchmarks. :). Source: over 4 years ago
  • [P] Database for AI: Visualize, version-control & explore image, video and audio datasets
    Hub, our open-source package, lets you stream datasets while training to PyTorch/TensorFlow. Check out how we achieved 95% GPU utilization while training on ImageNet at 50% less cost. We're building the Database for AI, with everything it should contain. If there's an adjacent feature that would make it more useful for your workflow, do let us know! Source: over 4 years ago
  • [P] Database for AI: Visualize, version-control & explore image, video and audio datasets
    I'm Davit from Activeloop (activeloop.ai). Source: over 4 years ago

What are some alternatives?

When comparing TerminusDB and Activeloop, you can also consider the following products

neo4j - Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.

Iterative.ai - Iterative removes friction from managing datasets and ML models and introduces seamless data scientists collaboration.

RedisGraph - A high-performance graph database implemented as a Redis module.

Pachyderm - Pachyderm is an open source analytics engine that uses Docker containers for distributed computations.

PlanetScale - The last database you'll ever need. Go from idea to IPO.

Scale - Get human tasks done with just one line of code.

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