
Apache Cassandra
MongoDB
Redis
ArangoDB
OrientDB
neo4j
PostgreSQL
CouchBase
TranscriptFetch
SocialFetch.dev
TranscriptAPI.com
TranscriptFetch is one API for getting text out of video and web content.
Send a URL from YouTube, TikTok, Instagram, X or Facebook and get back clean, timestamped text. Send any web page and get clean Markdown. One endpoint, one response shape, one API key.
Most short-form video has no caption track to download. TikTok's auto-captions are opt-in per upload, Instagram never publishes a downloadable track, and a large share of captions on both platforms are burned into the video frames where no parser can read them.
When there is no caption track, TranscriptFetch transcribes the audio instead. Same endpoint, same response, so your code never branches on which method produced the text.
text field for feeding a model or a search indexsegments array with per-cue start times and durations, so subtitles and jump-to-moment links are a formatting step rather than another integration100 free credits on signup, no card required. One credit per successful response. Failed, blocked and empty results are never charged, which matters on short-form video where a meaningful share of any batch is music with no speech in it.
Apache Cassandra
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TranscriptFetch's answer:
Most short-form video has no caption track to download. TikTokโs auto-captions are opt-in per upload, Instagram never publishes a downloadable track, and many captions on both are burned into the video frames where no parser can read them. TranscriptFetch transcribes the audio when no caption track exists, on the same endpoint, with the same response shape. Your code never branches on which method produced the text. It also covers YouTube, TikTok, Instagram, X and Facebook plus any web page as clean Markdown, so a pipeline spanning several sources is one integration rather than five.
TranscriptFetch's answer:
Three reasons. Coverage: one API key and one response shape across five video platforms and the open web, instead of stitching together a library per platform. Reliability: requests run through rotating infrastructure, so code that works locally keeps working from a server, which is where most open-source approaches break. Billing that matches reality: one credit per successful response, with failed, blocked and empty results never charged. That last point matters on short-form video, where a meaningful share of any batch is music with no speech in it. There is also an MCP server, so AI agents can fetch transcripts as a tool without a custom integration.
TranscriptFetch's answer:
Developers and technical teams building on video and web content. The common cases are RAG and retrieval pipelines that need video as text, AI agents that need to read a link mid-conversation, content teams repurposing short-form video at scale, and media monitoring and research tools. It is an API first, so the buyer is usually the person writing the integration rather than an end user. The free browser tools exist for one-off transcripts and for evaluating output quality before writing any code.
TranscriptFetch's answer:
It started with discovering there is no good way to get the text of a video. YouTubeโs official Data API will confirm a caption track exists and then refuse to hand it over, because captions.download requires the video ownerโs OAuth token. The popular open-source libraries work until you deploy them, at which point platforms start refusing datacenter IPs. And YouTube is the easy case: TikTok and Instagram publish no caption file at all. Every workaround solved one platform, worked locally, and broke in production. TranscriptFetch is the version that handles the failure cases as first-class behaviour rather than edge cases.
TranscriptFetch's answer:
Next.js with TypeScript and Tailwind on the front end and API layer, Clerk for auth with SHA-256 hashed API keys, Neon Postgres with Drizzle ORM, Redis for caching, and Stripe for billing. The extraction layer is a Python and FastAPI service. Speech-to-text uses Whisper-class models. The MCP server is published in the official Model Context Protocol registry with a DNS-verified namespace.
Based on our record, Apache Cassandra seems to be more popular. It has been mentiond 45 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.
When IoTDB was initiated in 2011, almost all influential distributed systems and databases were built in Java or on the JVMโsuch as Hadoop, HBase, Spark (Scala on JVM), Cassandra, Kafka, and Flink. To integrate deeply with the big data ecosystem, choosing Java was a natural decision. - Source: dev.to / 4 months ago
In fact, even in the absence of these commercial databases, users can effortlessly install PostgreSQL and leverage its built-in pgvector functionality for vector search. PostgreSQL stands as the benchmark in the realm of open-source databases, offering comprehensive support across various domains of database management. It excels in transaction processing (e.g., CockroachDB), online analytics (e.g., DuckDB),... - Source: dev.to / over 1 year ago
All messages are persisted durably for two minutes, but Pub/Sub channels can be configured to persist messages for longer periods of time using the persisted messages feature. Persisted messages are additionally written to Cassandra. Multiple copies of the message are stored in a quorum of globally-distributed Cassandra nodes. - Source: dev.to / over 1 year ago
Cassandra is a highly scalable, distributed NoSQL database designed to handle large amounts of data across many commodity servers without a single point of failure. - Source: dev.to / about 2 years ago
Distributed storage Distributed storage systems like Cassandra, DynamoDB, and Voldemort also use consistent hashing. In these systems, data is partitioned across many servers. Consistent hashing is used to map data to the servers that store the data. When new servers are added or removed, consistent hashing minimizes the amount of data that needs to be remapped to different servers. - Source: dev.to / about 2 years ago
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
SocialFetch.dev - Social media scraping API for public profiles, posts, comments, videos, transcripts, and metrics from TikTok, Instagram, YouTube, X, LinkedIn, and more. Pay-as-you-go credits, 100 free to start.
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
TranscriptAPI.com - Get YouTube video transcripts with a simple API call or through Model Context Protocol. Fast, reliable, and easy to integrate into your applications.
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
OrientDB - OrientDB - The World's First Distributed Multi-Model NoSQL Database with a Graph Database Engine.