Featured Data Shares

Birkini integrates structured data from verified providers across social platforms, markets, protocols, and user analytics. These datasets are ready to query, join, and analyze alongside your own.

Twitter Dataset

Includes posts, likes, reposts, and metadata from publicly available tweets and user profiles.

Structure:

  • profiles: user metadata

  • tweets: individual tweet-level data

Sample columns from profiles:

  • collect_timestamp: when the profile was captured

  • id: user ID

  • name, display_name, bio

  • is_blue_verified

  • created_timestamp

  • followers, following, tweets_count

  • location, profession_type, profession_categories

  • links, profile_image_url, banner_image_url

  • pinned_tweet_ids

Sample columns from tweets:

  • collect_timestamp, id, poster_id, text, timestamp

  • images, videos, hashtags, tagged_users

  • replies, reposts, likes, views, quotes, bookmarks

  • quote_parent_id, reply_conversation_id, retweet_parent_id, and related metadata

Utilities:

  • Tweet URL: https://twitter.com/i/web/status/{tweetId}

  • Profile URL: https://twitter.com/intent/user?user_id={userId}

CoinGecko Dataset

Historical and live data on all CoinGecko-listed assets.

Tables:

  • history: daily snapshots of asset performance

  • projects: metadata and market metrics for crypto assets

Sample columns from history:

  • DATE, COINGECKO_ID, FDMC, MARKET_CAP, PRICE, H24_VOLUME, SYMBOL

Sample columns from projects:

  • Circulating, total, and max supply

  • Market cap and price changes over time

  • All-time highs and lows with dates

  • Project name and symbol

DePIN Ninja Dataset

Project-level metrics and revenue history across DePIN infrastructure protocols.

Tables:

  • projects: static metadata

  • historical_revenue: time-series revenue data

Sample columns from projects:

  • projectId, name, category, chain

  • arr, mrr, createdAt

Sample columns from historical_revenue:

  • createdAt, date, name, projectId, revenue

Use cases include trend analysis, category-based comparisons, and financial performance benchmarking.

Slice Analytics Dataset

Segmentation of user activity and scoring for DEX, NFT, and Perp DEX platforms using proprietary behavior metrics.

Tables:

  • dex_trader_aggregates

  • nft_trader_aggregates

  • perps_trader_aggregates

Each table includes:

  • project, blockchain, user_count, avg_score

  • Distribution of user quality scores: users_over_50, users_over_60, ..._95

  • last_modified, id

This dataset is built for analyzing user quality beyond DAU metrics. It provides a richer view of protocol engagement through lifetime value, volume, and onchain behavior.

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