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docs/develop/java/spring/redis-and-spring-course/lesson_1/index-lesson_1.mdx

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- **RediSearch**: a full-featured search engine
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- **RedisGraph**: a graph database
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- **RedisTimeSeries**: a time-series database
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- **RedisAI**: a tensor and deep learning model server
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- **RedisJSON**: a native JSON data type
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- **RedisBloom**: native Bloom and Cuckoo Filter data types
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- **RedisGears**: a dynamic execution framework

docs/howtos/bert-qa-benchmarking/index-bert-qa-benchmarking-with-redisai-and-redisgears.mdx

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## Introduction
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In this article, we will explore the challenges and opportunities associated with deploying [large BERT Question Answering Transformer](https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad) models from Hugging Face, using [RedisGears](/howtos/redisgears) and [RedisAI](/howtos/redisai/getting-started) to perform a lot of the heavy lifting while also leveraging the in-memory datastore Redis.
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In this article, we will explore the challenges and opportunities associated with deploying [large BERT Question Answering Transformer](https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad) models from Hugging Face, using [RedisGears](/howtos/redisgears) and RedisAI to perform a lot of the heavy lifting while also leveraging the in-memory datastore Redis.
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## Why do we need RedisAI?
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docs/howtos/redisai/getting-started/index-gettingstarted.mdx

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