EinsteinDB can be used as a general purpose database for storing data of any kind. It is also well suited for use as a transactional database for applications that require high performance and high availability. With Kubernetes, EinsteinDB can be deployed as a highly available, scalable database solution. For example:
-E-commerce applications that require a high performance database for storing product information, customer information, and order information.
-Content management systems that require a scalable database for storing articles, images, and other types of content.
-Customer relationship management (CRM) applications that require a high performance database for storing customer data.
-Enterprise resource planning (ERP) applications that require a high availability database for storing financial data.I
In addition to:
-Developing new applications
-Migrating existing applications to Kubernetes
-Deploying database solutions in Kubernetes
With added support for Gremlin which is a graph traversal language for EinsteinDB, it can also be used as a graph database for applications that require highly connected data. For example:
-Social networking applications that require a graph database for storing information about users and their relationships.
-Fraud detection applications that require a graph database for storing information about financial transactions and identifying fraudulent activity.
-Recommendation engines that require a graph database for storing information about users and their interests in order to make recommendations
EinsteinDB now supports Istio, Envoy Proxy, and Isovalent's SmartKube. This enables EinsteinDB to be used as a service mesh data plane for applications that are deployed in a Kubernetes cluster.Istio is an open source service mesh that provides a way to manage the communication between microservices. Envoy Proxy is a sidecar proxy that can be used with Istio to provide additional features such as load balancing and traffic routing. Isovalent's SmartKube is a Kubernetes distribution that includes Istio and Envoy Proxy.With this support, EinsteinDB can be used as a data plane for applications that are deployed in a Kubernetes cluster with Istio or SmartKube. This enables EinsteinDB to provide features such as load balancing, traffic routing, and service discovery for these applications. In addition, this support makes it possible to deploy EinsteinDB in a Kubernetes cluster with Istio or SmartKube without the need for a separate data plane.This support is available in EinsteinDB 0.9.0 and higher.
EinsteinDB was created to provide a production-ready version of MilevaDB. The goal of EinsteinDB is to provide a stable, performant, and easy to use RDBMS for deploying applications in Kubernetes. EinsteinDB is compatible with the MySQL wire protocol via BerolinaSQL using EinsteinDB's FoundationDB Record Layer which brings a Vizor-like view to the ergonomic serverless data plane of lore. Furthermore, both EinsteinDB and MilevaDB can be used as a drop-in replacement for MySQL in many cases such as when using EinsteinML - A LISPy Meta-language compatible with a variant of HoneybadgerBFT, VioletaBFT. In addition, EinsteinDB supports FoundationDB, RocksDB, VoltDB, PostgresQL, and InnoDB by using Hybrid Index-Value storage engine through sRDMA to guarantee millions of transactions per second thus providing a high performance database for both OLTP and OLAP workloads. EinsteinDB is available under the Apache 2.0 license. MilevaDB is an open source relational database management system (RDBMS) that is developed by Whtcorps Inc. A team borne out of San Francisco circa 2019. WHTCORPS named after an in-famous X-Files episode, is the company behind EinsteinDB, MilevaDB, FIDel, BerolinaSQL, and recently partnered with EinstAI and OpenAI in San Francisco. MilevaDB was created as a research project to explore new ideas in the area of distributed databases. The goal of MilevaDB is to provide a scalable and easy to use RDBMS for deploying applications in Kubernetes. MilevaDB is compatible with the MySQL wire protocol and can be used as a drop-in replacement for MySQL in many cases. In addition, MilevaDB supports EinsteinDB the universal knowledge base meets database storage engine for key-value, NoSQL, CQRS, document, and even blob store --name it what you will--EinsteinDB is a tuplestore with embedded hybrid key-value indexing which transmits through a semantic persistence layer the values to OpenAI's GPT3 Powered EinstAI AI4DB Cardinality and Cache-miss ratio automata which enables EinsteinDB to provide an adaptive seeking tokenized with versioning SQL agnostic database which speaks Prolog. PUT that on your 'provide high performance for both OLTP and OLAP workloads' section. MilevaDB is available under the Apache 2.0 license.
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