55 docs tagged with "Community"

The ScalarDB library is available on the Maven Central Repository. You can add the library as a build dependency to your application by using Gradle or Maven.

This guide explains how to back up and restore databases that are used by ScalarDB.

This document explains how to configure the underlying databases of ScalarDB to make applications that use ScalarDB work correctly and efficiently.

This document explains how to create your custom values file for the ScalarDB Analytics with PostgreSQL chart. For details on the parameters, see the README of the ScalarDB Analytics with PostgreSQL chart.

Consensus Commit is the transaction protocol used in ScalarDB and is designed for executing transactions spanning multiple diverse databases. Its uniqueness is that the protocol achieves ACID transactions without relying on the transaction capabilities of the underlying databases, unlike X/Open XA-based solutions. This document explains the details of the protocol, including how it works, the guaranteed isolation levels, the interfaces, the performance optimization that it employs, and its limitations.

This tutorial describes how to create a sample application that supports microservice transactions in ScalarDB.

This tutorial describes how to create a sample application that supports the multi-storage transactions feature in ScalarDB.

In this category, you can follow guides to help you become more familiar with deploying ScalarDB, specifically ScalarDB Cluster and ScalarDB Analytics, in local and cloud-based Kubernetes environments.

In this category, you can follow guides to help you become more familiar with ScalarDB, specifically with how to run transactions, analytical queries, and non-transactional storage operations.

This document explains how you can get started with the ScalarDB Data Loader Export function.

This document explains how to get started with log aggregation for Scalar products on Kubernetes using Grafana Loki (with Promtail).

This document explains how to get started with Scalar products monitoring on Kubernetes using Prometheus Operator (kube-prometheus-stack). Here, we assume that you already have a Mac or Linux environment for testing. We use Minikube in this document, but the steps we will show should work in any Kubernetes cluster.

This guide explains how to get started with ScalarDB Analytics with PostgreSQL by using a Helm Chart in a Kubernetes cluster as a test environment. In addition, the contents of this guide assume that you already have a Mac or Linux environment set up for testing. Although minikube is mentioned, the steps described should work in any Kubernetes cluster.

This document explains how you can get started with the ScalarDB Data Loader Import function.

This getting started tutorial explains how to configure your preferred database in ScalarDB and illustrates the process of creating a sample e-commerce application, where items can be ordered and paid for with a credit card by using ScalarDB. The sample e-commerce application shows how users can order and pay for items by using a line of credit.

This document explains how to get started with ScalarDB Analytics with PostgreSQL. We assume that you have already installed ScalarDB Analytics with PostgreSQL and that all required services are running. If you don't have such an environment, please follow the instructions in How to Install ScalarDB Analytics with PostgreSQL in Your Local Environment by Using Docker. Because ScalarDB Analytics with PostgreSQL executes queries via PostgreSQL, we also assume that you already have a psql client or another PostgreSQL client to send queries to PostgreSQL.

This getting started tutorial explains how to configure your preferred database in ScalarDB and set up a basic electronic money application by using Kotlin. Since Kotlin has Java interoperability, you can use ScalarDB directly from Kotlin.

This glossary includes database and distributed-system terms that are often used when using ScalarDB.

Since ScalarDB provides transaction capabilities on top of non-transactional or transactional databases non-invasively, you need to take special care to back up and restore the databases in a transactionally consistent way.

This document explains how to deploy ScalarDB Analytics with PostgreSQL by using Scalar Helm Charts. For details on the custom values file for ScalarDB Analytics with PostgreSQL, see Configure a custom values file for ScalarDB Analytics with PostgreSQL.

This document explains how to set up a local environment that runs ScalarDB Analytics with PostgreSQL using the multi-storage back-end of Cassandra, PostgreSQL, and DynamoDB local server using Docker Compose.

This guide explains how to scale ScalarDB. The contents of this guide assume that you used Scalar Helm Chart to deploy ScalarDB Cluster, which is the recommended way.

This guide explains how to upgrade to a newer version of ScalarDB.

You might want to use ScalarDB (e.g., for database-spanning transactions) with your existing databases. In that case, you can import those databases under the ScalarDB control using ScalarDB Schema Loader. ScalarDB Schema Loader automatically adds ScalarDB-internal metadata columns in each existing table and metadata tables to enable various ScalarDB functionalities including transaction management across multiple databases.

In this category, you can follow guides to help you manage ScalarDB.

For details on importing your tables or migrating your applications and databases to a ScalarDB-based environment, see the following guides:

Data modeling (or in other words, designing your database schemas) is the process of conceptualizing and visualizing how data will be stored and used by identifying the patterns used to access data and the types of queries to be performed within business operations.

ScalarDB transactions can span multiple storages or databases while maintaining ACID compliance by using a feature called multi-storage transactions.

In this category, you can follow quickstart tutorials for how to get started with running transactions and queries through ScalarDB.

This page describes the required tools and their versions to use ScalarDB correctly.

This tutorial describes how to run analytical queries on sample data by using ScalarDB Analytics with PostgreSQL.

ScalarDB was initially designed to provide a unified abstraction between diverse databases and transactions across such databases. However, there are cases where you only need the unified abstraction to simplify your applications that use multiple, possibly diverse, databases.

This guide explains how to run non-transactional storage operations through the ScalarDB Core library.

This page explains how to run non-transactional storage operations through the primitive CRUD interface, also known as the Storage API. This guide assumes that you have an advanced understanding of ScalarDB.

In this sub-category, you can learn how to run various sample applications that take advantage of ScalarDB.

In this sub-category, you can learn how to model your data based on the ScalarDB data model and create schemas. Then, you can learn how to run transactions through the ScalarDB Core library and ScalarDB Cluster, a gRPC server that wraps the Core library.

This guide explains how to configure your ScalarDB properties file and create schemas to run transactions through a one-phase or a two-phase commit interface by using the ScalarDB Core library.

This page includes a list of release notes for ScalarDB 3.16.

In this sub-category, you can see tutorials on how to run analytical queries over the databases that you write through ScalarDB by using a component called ScalarDB Analytics.

This tutorial describes how to run benchmarking tools for ScalarDB. Database benchmarking is helpful for evaluating how databases perform against a set of standards.

This page describes the available configurations for ScalarDB Core.

This page provides a list of error codes in ScalarDB Core.

In this sub-category, you can follow tutorials on how to run ACID transactions through the ScalarDB Core library, which is publicly available under the Apache 2 license.

This page provides a list of error codes in ScalarDB Data Loader.

This document briefly explains the design and implementation of ScalarDB. For what ScalarDB is and its use cases, see ScalarDB Overview.

ScalarDB FDW is a PostgreSQL extension that implements a foreign data wrapper (FDW) for ScalarDB.

This document briefly explains which features are available in which editions of ScalarDB.

The ScalarDB Java API is mainly composed of the Administrative API and Transactional API. This guide briefly explains what kinds of APIs exist, how to use them, and related topics like how to handle exceptions.

This page describes what ScalarDB is and its primary use cases.

This roadmap provides a look into the proposed future of ScalarDB. The purpose of this roadmap is to provide visibility into what changes may be coming so that you can more closely follow progress, learn about key milestones, and give feedback during development. This roadmap will be updated as new versions of ScalarDB are released.

ScalarDB has its own data model and schema that maps to the implementation-specific data model and schema. In addition, ScalarDB stores internal metadata, such as transaction IDs, record versions, and transaction statuses, to manage transaction logs and statuses when you use the Consensus Commit transaction manager.

This page provides a list of error codes in ScalarDB Schema Loader.

Schema Importer is a CLI tool for automatically configuring PostgreSQL. By using this tool, your PostgreSQL database can have identical database objects, such as namespaces and tables, as your ScalarDB instance.

ScalarDB supports executing transactions with a two-phase commit interface. With the two-phase commit interface, you can execute a transaction that spans multiple processes or applications, like in a microservice architecture.