Ingres connectivity
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This document discusses various ways to connect to Ingres databases from client applications. It describes connecting locally or remotely from an Ingres client, through ODBC, JDBC, or data access servers. Gateways are also covered, which allow Ingres databases to connect to non-Ingres databases locally or remotely. Finally, Ingres Star is summarized as providing a way to create a single federated database that connects to both local Ingres and remote non-Ingres data sources.
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This document summarizes a company's transition from a SQL database to a native graph database to power their identity resolution product. It describes the requirements of high read and write throughput and complex queries over billions of identities and linkages. It then outlines the evaluation of several graph databases, with JanusGraph on ScyllaDB performing the best. Key findings from prototyping include handling high query volume, managing supernodes, and tuning compaction strategies. The production implementation and architecture is also summarized.
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The document summarizes the journey of migrating from an RDBMS to MongoDB. It describes the pre-MongoDB RDBMS environment, reasons for choosing MongoDB, and the evolution of the MongoDB environment over time. The evolution involved some bumps in configuring databases and applications, but also many breezes like improved performance, flexibility and scalability. Benchmarking showed MongoDB could handle more concurrent users. Future plans include using MongoDB 4.0 features and further optimizing sharding performance.
Improve PostgreSQL replication with Oracle GoldenGate
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Discussion on Datadog’s experiences, both successes and challenges, as they built our monitoring solutions on top AWS Lambda and Amazon API gateway with the goal of reducing latency and increasing performance while cutting infrastructure costs.
Elevate MongoDB with ODBC/JDBC
<b>Elevate MongoDB with ODBC/JDBC </b>[4:05 pm - 4:25 pm]<br />Adoption for MongoDB is growing across the enterprise and disrupting existing business intelligence, analytics and data integration infrastructure. Join us to disrupt that disruption using ODBC and JDBC access to MongoDB for instant out-of-box integration with existing infrastructure to elevate and expand your organization’s MongoDB footprint. We'll talk about common challenges and gotchas that shops face when exposing unstructured and semi-structured data using these established data connectivity standards. Existing infrastructure requirements should not dictate developers’ freedom of choice in a database
Eagle6 mongo dc revised
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Eagle6 Enterprise Situational Awareness
Eagle6 is a product that use system artifacts to create a replica model that represents a near real-time view of system architecture. Eagle6 was built to collect system data (log files, application source code, etc.) and to link system behaviors in such a way that the user is able to quickly identify risks associated with unknown or unwanted behavioral events that may result in unknown impacts to seemingly unrelated down-stream systems. This session is designed to present the capabilities of the Eagle6 modeling product and how we are using MongoDB to support near-real-time analysis of large disparate datasets.
Owning End-to-end Application Experience With ThousandEyes
The document discusses digital experiences and application performance monitoring. It notes that digital usage is increasing rapidly, with 500 million new apps expected by 2023. Users expect perfect digital experiences and will abandon apps or services with poor performance. However, applications have become more complex with dependencies on services, APIs, cloud infrastructure and the internet itself. To truly understand performance, the entire digital supply chain from user to backend must be monitored, including factors like DNS lookups, BGP routing, and CDN delivery. The document advocates for an approach that provides end-to-end visibility across networks and applications.
gRPC or Rest, why not both?
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Rate Limiting GQLs Using Depth and Complexity Analysis
GraphQL is gaining popularity due to the flexibility associated with its usage. Since different users will have different query requirements, GraphQL APIs require rate limiting policies that provide users the flexibility to query required data whilst protecting itself from being overwhelmed.
When using GraphQL APIs, its declarative nature of data retrieval enables users to query the exact amount of data required without under fetching or over fetching. Since different queries have different data load and computational complexities, using traditional request count based rate-limiting policies is ill-suited for GraphQL APIs. When enforcing rate-limiting policies to these APIs it is imperative to ensure that it will not hinder the user’s ability to query data. This can be achieved by categorizing users based on their query requirements and introducing rate-limiting policies for each category based on the depth and complexity of their query requirement. WSO2 API Manager consists of a Static Query Analyser which can enforce rate limiting to GraphQL APIs using both depth and complexity analysis.
This slide deck explores how you can protect GraphQL backends using rate limiting.
On-demand webinar: https://wso2.com/library/webinars/rate-limiting-gqls-using-depth-and-complexity-analysis/
MongoDB SoCal 2020: Migrate Anything* to MongoDB Atlas
This presentation discusses migrating data from other data stores to MongoDB Atlas. It begins by explaining why MongoDB and Atlas are good choices for data management. Several preparation steps are covered, including sizing the target Atlas cluster, increasing the source oplog, and testing connectivity. Live migration, mongomirror, and dump/restore options are presented for migrating between replicasets or sharded clusters. Post-migration steps like monitoring and backups are also discussed. Finally, migrating from other data stores like AWS DocumentDB, Azure CosmosDB, DynamoDB, and relational databases are briefly covered.
Ember Data Introduction and Basic Concepts
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How R Developers Can Build and Share Data and AI Applications that Scale with...
This document discusses how R developers can build and share scalable data and AI applications using RStudio and Databricks. It outlines how RStudio and Databricks can be used together to overcome challenges of processing large amounts of data in R, including limited server memory and performance issues. Developers can use hosted RStudio servers on Databricks clusters, connect to Spark from RStudio using Databricks Connect, and share scalable Shiny apps deployed with RStudio Connect. The ODBC toolchain provides a performant way to connect R to Spark without issues encountered when using sparklyr directly.
New Features in MongoDB Atlas
Speaker: Cory Mintz, Lead Engineer, MongoDB
It has been one year since MongoDB Atlas was revealed at MongoDB World 2016. In this session lead Atlas engineer Cory Mintz will walk you through new Atlas features that have been built over the last year, how they work under the hood, and some of the implementation challenges that the team faced. Cory will discuss the building blocks of IaaS providers and how we leverage them in Atlas. VPC peering and Live Import are on the agenda, as well as features so new that you will hear them announced at MongoDB World.
What You Will Learn:
- How to use the latest features in MongoDB Atlas
Introducing Stitch
Speaker: Drew DiPalma, Product Manager, Cloud, MongoDB
Level: 100 (Beginner)
Track: Developer
Come learn more about MongoDB Stitch – Our new Backend as a Service (BaaS) that makes it easy for developers to create and launch applications across mobile and web platforms. Stitch provides a REST API on top of MongoDB with read, write, and validation rules built-in and full integration with the services you love. This talk will cover the what, why, and how of MongoDB Stitch. We’ll discuss everything from features to the architecture. You’ll walk away knowing how Stitch can kickstart your new project or take your existing application to the next level.
What You Will Learn:
- The basics of MongoDB Stitch and how to use it to kickstart new projects and implement new features in existing projects.
- How to integrate your favorite services with your MongoDB application without writing any code.
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Using Kafka to stream data into TigerGraph, a distributed graph database, is a common pattern in our customers’ data architecture. In the TigerGraph database, Kafka Connect framework was used to build the native S3 data loader. In TigerGraph Cloud, we will be building native integration with many data sources such as Azure Blob Storage and Google Cloud Storage using Kafka as an integrated component for the Cloud Portal.
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I talk about the short url project we did internally.
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Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
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Ingres connectivity
- 2. Ingres Architecture Ingres Client : Server connectivity ODBC : Ingres Connectivity JDBC : Ingres Connectivity Ingres Client: Non-Ingres Database Ingres Star Connectivity to Ingres and Non-Ingres Databases Agenda
- 3. Ingres Client - Local Server Connection Ingres Database Communication Server GCA Name server GCA Ingres User interface G C A DBMS server G C A c a c h e Local Ingres Server Remote Ingres Server Ingres User interface G C A Connect to a local Ingres database, eg. isql foodb Connect to a remote Ingres database, eg. isql remote::demodb
- 4. Remote Ingres Server Ingres Client – Remote Server Connection Ingres Database Communication Server GCA Name server GCA DBMS server G C A c a c h e Ingres Client Data Access Server GCA Ingres User interface G C A Communication Server GCA Ingres Local Client G C A Connection from a client to a remote Ingres database
- 5. Remote Ingres Server Name server GCA ODBC Client – Remote Server Connection Communication Server GCA Ingres ODBC/Driver G C A ODBC Client ODBC Client Communication Server GCA DBMS server G C A c a c h e Data Access Server GCA Ingres Local Client G C A Ingres Database Ingres Clients Connection from an ODBC client to a remote Ingres database
- 6. Remote Ingres Server Data Access Client: Remote Server Connection DAS Client JDBC/.NET/PHP etc Client Communication Server GCA DBMS server G C A c a c h e Data Access Server GCA ODBC Clients Ingres Local Client G C A Name server GCA Ingres Database Ingres Clients Connection from non- Ingres client (eg Java, .NET) to a remote Ingres database
- 7. Remote Ingres Server Ingres Server Connection Summary Communication Server GCA DBMS server G C A c a c h e Data Access Server GCA Ingres Clients Ingres Local Clients G C A Name server GCA Ingres Database ODBC ClientsDAS Clients
- 8. Ingres Connection to Local Gateway Ingres Gateway Server GCA Ingres User interface G C A MSSQL Database Connect to a local non- Ingres database Name server GCA
- 9. Ingres Connection to Remote Gateway Ingres Database Communication Server GCA Ingres User interface G C A DBMS server G C A c a c h e Ingres Server MSSQL Database Communication Server GCA MSSQL Server Ingres Gateway Server GCA Ingres User interface G C A Name server GCA Connect to a local Ingres database Connect to a remote non-Ingres Database
- 10. Ingres Star Database with Gateways Ingres Star Database Communication Server GCA Ingres User interface G C A Star/ DBMS server G C A Ingres Server MSSQL Database(s) Communication Server GCA MSSQL Server Ingres Gateway Server GCA Ingres Database(s) Name server GCA Connect to a local Ingres Star database which has links to a local Ingres tables and to remote non-Ingres tables
- 11. http://community.ingres.com/wiki/... – Connect to a local Ingres database • …/Connect_To_Ingres_Database_Using_ISQL – Connect to a remote Ingres database • …/Connect_Ingres_Client – Connect ODBC to an Ingres Database • .../Workshops/Connect/IngresODBC – Connect to a remote database using JDBC • …/Squirrel_Howto – Use Ingres Star to federate local and remote databases • …/CreateStarDatabase Ingres Workshops. Find out How To …