Rockset

APRIL 18, 2023

To highlight these new capabilities, we built a search demo using OpenAI to create embeddings for Amazon product descriptions and Rockset to generate relevant search results. With vector search, we can leverage text embeddings to capture semantic associations across words, phrases and sentences to power more robust search experiences.

Unstructured Data 105

Unstructured Data Metadata Machine Learning SQL 105

Christophe Blefari

APRIL 19, 2024

Hydra: the Postgres data warehouse — Postgres is one of the most used database, this week I discovered Hydra an open-source columnar port of Postgres aiming to create an open-source Snowflake. Snowflake text embeddings for retrieval. Neon GA — Neon, another Postgres fork, is generally available.

MySQL 130

MySQL Data Datasets SQL 130

Towards Data Science

JULY 13, 2023

The example we’ll walk you through will mirror a typical LLM application workflow you’d run to populate a vector database with some text knowledge. Specifically, we’ll cover pulling data from the web, creating text embeddings (vectors) and pushing them to a vector store. Disclaimer: I’m one of the authors of the Hamilton package.

Building 73

Building Database-centric Database Coding 73

Monte Carlo

MARCH 7, 2024

Why prompt engineering isn’t all that and a bag of SQL queries Understand vector databases Create AI differentiation with RAG Find and solve real business problems High-quality data always lives up to the hype What is prompt engineering? Table of Contents Why is prompt engineering important?

Engineering 59

Engineering High Quality Data Database Architecture 59

Edureka

APRIL 19, 2024

Step 8) Add Embeddings to the vector store To add embeddings, return to add nodes, select embeddings, pick “OpenAI Embeddings,” drag it onto the canvas, and then link it to the vector store.

Building 52

Building Engineering Coding Systems 52

Christophe Blefari

JULY 22, 2023

LLM based pipelines with PostgresML and dbt — Mainly for me this is a discovery of the PostgresML an open-source extension that brings ML functions to the database. As cloud databases like Snowflake and BigQuery brought it years ago, this was mandatory for the Postgres stack.

Data 130

Data Database Big Data Data Engineering 130

Data Engineering Podcast

OCTOBER 30, 2022

In this episode Amir Orad discusses the Sisense platform and how it facilitates the embedding of analytics and data insights in every aspect of organizational and end-user experiences. What are the unique capabilities that Sisense offers compared to other BI or embedded analytics services?

Business Intelligence 130

Business Intelligence Metadata MongoDB MySQL 130

Monte Carlo

JANUARY 3, 2024

They need to know prompt engineering , vector databases and embedding vectors , data modeling, data orchestration , data pipelines and all for RAG. The database has to be a trusted source that includes proprietary data, and it allows the model to incorporate up-to-date and reliable information into its responses and reasoning.

Technology 113

Technology Database Data Governance Data Engineering 113

Towards Data Science

DECEMBER 1, 2023

Why static workload is insufficient and what I learned by comparing HNSWLIB and DiskANN using streaming workload Image by DALLE-3 Vector databases are built for high-dimensional vector retrieval. Embeddings are used in many applications like search engines, recommendation systems, and chatbots. O(log n) ) with respect to index size.

Database 52

Database Algorithm Datasets Kafka 52

Rockset

SEPTEMBER 26, 2023

Models may need to know about events, computed metrics, and embeddings based on locality. The recommendation engine needs user, seller, livestream, computed metrics, and embeddings as a diverse set of real-time inputs. We aim to coherently feed these diverse inputs into a model with low latency and without a complex architecture.

Metadata 64

Metadata Kafka Cloud Database 64

Christophe Blefari

SEPTEMBER 1, 2023

After Excel, Notebooks get a second youth — Meta explained how they schedule Jupyter Notebooks in production , Google announced the BigQuery studio with embedded Notebooks in the UI and Jupyter released Jupyter AI (you call it with %ai ) to bring Gen AI to the notebook. New features in Airflow — with 2.7 Consolidation.

Food 130

Food Data SQL Python 130

Monte Carlo

FEBRUARY 27, 2024

With RAG, when a customer makes an inquiry about an order, the system can retrieve their specific details from the database and generate a response with relevant follow-up options, like tracking a shipment or managing returns. The RAG chain starts with a user query, which triggers the system to fetch relevant data from the database.

Data Engineering 59

Data Engineering Data Engineer Engineering High Quality Data 59

Monte Carlo

NOVEMBER 9, 2023

Hallucinations are caused by a variety of factors from poor embeddings to knowledge cutoff, and frequently affect the quality of responses generated by publicly available or open LLMs trained on information scraped from the internet, which account for most models. All of these currently exist in databases and data warehouses.

Unstructured Data 86

Unstructured Data Database Data Pipeline Architecture 86

Knowledge Hut

DECEMBER 22, 2023

The report can even be embedded in an external site, or the links of the report could be shared via Outlook. Access to the latest features for embedded analytics, One API surface, and a consistent set of capabilities. For example, an answer to a question like what was the total sales last year?

BI 98

BI Business Intelligence Machine Learning Data Cleanse 98

Christophe Blefari

FEBRUARY 24, 2023

Stream processing vs real-time OLAP vs streaming database — Data storage  + compute field is slowly becoming a mess a lot of technologies that are so close but so far away at the same time. Shark attacks visualisation — This is a great example of embedded analytics.

Kafka 130

Kafka Data Lake Data Storage Data 130

DataKitchen

FEBRUARY 27, 2024

Retrieval-Augmented Generation: Enhancing LLMs with Targeted Data Retrieval-augmented generation (RAG) is a methodology where an LLM generates outputs based on the input prompt and leverages an external database or repository of information. Embedding: The retrieved data is encoded into embeddings that the LLM can interpret.

Data Engineering 48

Data Engineering Data Engineer Engineering Unstructured Data 48

Data Engineering Podcast

AUGUST 21, 2022

With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Just connect it to your database/data warehouse/data lakehouse/whatever you’re using and let them do the rest.

Lambda Architecture 100

Lambda Architecture MongoDB Scala MySQL 100

Rockset

OCTOBER 13, 2023

When building a vector search app, you’re going to end up managing a lot of vectors, also known as embeddings. A vector database not only stores embeddings but also facilitates such common search operations over them. Every item you want to search on will need to be processed to produce an embedding, as will every query.

Database 52

Database Metadata Algorithm Cloud 52

Christophe Blefari

JANUARY 20, 2023

But, funny, in the end we are still copying data from database to database by using CSVs, like 40 years ago. Embedded analytics is the capabilities to introduce Business Intelligence apps within "traditional" software platforms like SaaS application or public website. Data Economy 💰 Cumul.io

Google Cloud 130

Google Cloud Data Hadoop Business Intelligence 130

Tweag

FEBRUARY 5, 2024

Despite the hype around vector databases and semantic search, the problem of knowledge indexing is still far from being solved. An embedding model is used to “vectorize” these chunks. These vectors are indexed into a vector database. Upon receiving a query: The query is vectorized using the same embedding model.

Database 60

Database Machine Learning Systems Software Engineer 60

Workfall

OCTOBER 3, 2023

What is MySQL Database? CRUD represents Create, Read/Retrieve, Update, and Delete – fundamental actions on persistent storage, aligned with HTTP methods used in web development and database management: – POST: Establishes a fresh resource. What is MySQL Database? What is Spring Boot? – DELETE: Removes a resource.

MySQL 85

MySQL Database Java Programming Language 85

Scott Logic

FEBRUARY 26, 2023

Since we are using Spring Boot, you would probably be extending an interface such as CrudRepository or MongoRepository based on your choice of database to create the repositories. I have a PostgreSQL database in my production, and now you are asking me to test with a H2? Wait what?? Alright, then what should I do? Yes, why not?

MongoDB 75

MongoDB PostgreSQL Consulting Java 75

Striim

AUGUST 29, 2023

We are proud to announce that Striim has successfully achieved Google Cloud Ready – Cloud SQL Designation for Google Cloud’s fully managed relational database service for MySQL, PostgreSQL, and SQL Server.

Google Cloud 52

Google Cloud SQL Cloud Designing 52

Rockset

OCTOBER 21, 2022

You’ll also need a transactional database to store customers’ transactions and personal information. Real-time database that handles bursty data streams: You need a database that separates ingest compute, query compute, and storage. Rockset is one of the few databases that separate ingest and query compute, and storage.

Kafka 52

Kafka Building SQL Database 52

Rockset

APRIL 26, 2023

In part 2 we covered the differences between real-time analytics databases and stream processing. Our examples will all feature Rockset, but you can swap it out for other RTA databases, with a few use-case-specific caveats. This could be a cloud data warehouse, a data lake, or a database. The database has two primary jobs.

Architecture 52

Architecture Transportation Data Lake Insurance 52

Data Engineering Weekly

AUGUST 6, 2023

The goal of the Spark RDD framework is to minimize the data shuffle, as the dbt can potentially minimize the number of database calls. link] Microsoft: Decoding the customer journey with graph node embeddings Is a Graph a better data structure to model than a tabular model? I think so, so does the author.

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

Data Engineering Podcast

JUNE 12, 2022

With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. No more shipping and praying, you can now know exactly what will change in your database!

Metadata 100

Metadata Unstructured Data Business Intelligence MongoDB 100

Knowledge Hut

OCTOBER 26, 2023

You can link the project to a database in the background to collect information. Hotel Booking System The hotel booking system is an easy-to-use system with a centralized database programming procedure. This also necessitates extensive networking skills, including the ability to retrieve and show information from the database.

Coding 52

Coding Project Programming Language MySQL 52

Mutt Data

SEPTEMBER 24, 2023

And it doesn’t just stop at choosing a model: there is an accompanying set of supporting tools like LLamaIndex, LangChain or Vector Databases. These embeddings later get stored in a vector database. Infrastructure: these models have to be trained and then deployed into the real world.

Machine Learning 40

Machine Learning Software Engineer Software Engineering Database 40

Ascend.io

JUNE 22, 2023

DuckDb powers Ascend’s advanced, user-friendly data pipeline observability features – a perfect example of an embedded analytics use case! Getting Started All you need to establish a connection to MotherDuck in Ascend is the name of your MotherDuck database and your credential token!

NoSQL 52

NoSQL MySQL Google Cloud Data Pipeline 52

Data Engineering Podcast

JUNE 3, 2018

Summary Using a multi-model database in your applications can greatly reduce the amount of infrastructure and complexity required. In this episode Jan Steeman and Jan Stücke explain where Arango fits in the crowded database market, how it works under the hood, and how you can start working with it today.

Data Storage 100

Data Storage PostgreSQL Architecture Database 100

Data Engineering Podcast

OCTOBER 14, 2019

You listen to this show to learn and stay up to date with what’s happening in databases, streaming platforms, big data, and everything else you need to know about modern data management. What was your selection process for an embedded runtime and how did you decide on javascript?

Data Warehouse 100

Data Warehouse PostgreSQL AWS Programming Language 100

Mutt Data

SEPTEMBER 26, 2023

Navigating this landscape requires not just model selection, but fluency in tools like LLamaIndex, LangChain, and Vector Databases in order to build complete solutions. Infrastructure: AI models can either be built and trained from scratch using GPUs or leveraged through pre-existing APIs.

Machine Learning 40

Machine Learning Architecture Software Engineer Software Engineering 40

Mutt Data

SEPTEMBER 26, 2023

Navigating this landscape requires not just model selection, but fluency in tools like LLamaIndex, LangChain, and Vector Databases in order to build complete solutions. Infrastructure: AI models can either be built and trained from scratch using GPUs or leveraged through pre-existing APIs.

Machine Learning 40

Machine Learning Architecture Software Engineer Software Engineering 40

Knowledge Hut

APRIL 19, 2023

Software engineers can work on a variety of endeavors, including enterprise software, embedded systems, desktop applications, and mobile apps. Delivers Web pages, user interfaces, web applications, web services, and database designs. They deliver web pages, user interfaces, web applications, web services, and database designs.

Software Engineer 59

Software Engineer Software Engineering Engineering Computer Science 59