---
type: Concept
title: Glossary
description: This glossary includes database and distributed-system terms that are often used when using ScalarDB.
resource: https://scalardb.scalar-labs.com/docs/latest/glossary/
tags:
- scalardb
- v3.19
- phase:design
- edition:community
- edition:enterprise-standard
- edition:enterprise-premium
status: stable
product: scalardb
product_title: ScalarDB
version: '3.19'
patch_version: 3.19.0
doc_id: glossary
lifecycle_phase: design
editions:
- Community
- Enterprise Standard
- Enterprise Premium
generated:
  by: process:okf-build/1.0.0
  at: '2026-08-10T20:39:58Z'
sources:
- id: docs-scalardb
  resource: https://github.com/scalar-labs/docs-scalardb/blob/8bb9295f8fbd8a042360ebb5a3e70f8c4e5dfa47/docs/glossary.mdx
  title: ScalarDB documentation source (MDX)
  author: process:scalar-labs/docs-scalardb
  last_modified: '2026-08-07T16:37:01Z'
---

# Glossary

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

## ACID

Atomicity, consistency, isolation, and durability (ACID) is a set of properties that ensure database transactions are processed reliably, maintaining integrity even in cases of errors or system failures.

## concurrency control

Concurrency control in databases ensures that multiple transactions can occur simultaneously without causing data inconsistency, usually through mechanisms like locking or timestamp ordering.

## consensus

Consensus in distributed systems refers to the process of achieving agreement among multiple computers or nodes on a single data value or system state.

## data federation

Data federation is the process of integrating data from different sources without moving the data, creating a unified view for querying and analysis.

## data mesh

A data mesh is a decentralized data architecture that enables each business domain within a company to autonomously manage data and use it efficiently.

## data virtualization

Data virtualization is similar to data federation in many aspects, meaning that it virtualizes multiple data sources into a unified view, simplifying queries without moving the data.

## database anomalies

Database anomalies are inconsistencies or errors in data that can occur when operations such as insertions, updates, or deletions are performed without proper transaction management.

## federation engine

A federation engine facilitates data integration and querying across multiple disparate data sources, often as part of a data federation architecture.

## global transaction

A global transaction spans multiple databases or distributed systems and ensures that all involved systems commit or roll back changes as a single unit.

## heterogeneous databases

Heterogeneous databases refer to systems composed of different database technologies that may have distinct data models, query languages, and transaction mechanisms.

## HTAP

Hybrid transactional/analytical processing (HTAP) refers to a system that can handle both transactional and analytical workloads concurrently on the same data set, removing the need for separate databases.

## JDBC

Java Database Connectivity (JDBC) is an API that allows Java applications to interact with databases, providing methods for querying and updating data in relational databases.

## linearizability

Linearizability is a strong consistency model in distributed systems where operations appear to occur atomically in some order, and each operation takes effect between its start and end.

## NoSQL database

A NoSQL database is a non-relational databases designed for specific data models, such as document, key-value, wide-column, or graph stores, often used for handling large-scale, distributed data.

## Paxos

Paxos is a family of protocols used in distributed systems to achieve consensus, even in the presence of node failures.

## PITR

Point-in-time recovery (PITR) allows a database to be restored to a previous state at any specific time, usually after an unintended event like data corruption.

## polystores

Polystores are database architectures that allow users to interact with multiple, heterogeneous data stores, each optimized for a specific workload or data type, as if they were a single system.

## read-committed isolation

Read-committed isolation is an isolation level where each transaction sees only committed data, preventing dirty reads but allowing non-repeatable reads.

## relational database

A relational database stores data in tables with rows and columns, using a structured query language (SQL) to define, query, and manipulate the data.

## replication

Replication in databases involves copying and distributing data across multiple machines or locations to ensure reliability, availability, and fault tolerance.

## Saga

The Saga pattern is a method for managing long-running transactions in a distributed system, where each operation in the transaction is followed by a compensating action in case of failure.

## serializable isolation

Serializable isolation (serializability) is the highest isolation level in transactional systems, ensuring that the outcome of concurrently executed transactions is the same as if they were executed sequentially.

## snapshot isolation

Snapshot isolation is an isolation level that allows transactions to read a consistent snapshot of the database, protecting them from seeing changes made by other transactions until they complete.

## TCC

Try-Confirm/Cancel (TCC) is a pattern for distributed transactions that splits an operation into three steps, allowing for coordination and recovery across multiple systems.

## transaction

A transaction in databases is a sequence of operations treated as a single logical unit of work, ensuring consistency and integrity, typically conforming to ACID properties.

## transaction manager

A transaction manager coordinates the execution of transactions across multiple systems or databases, ensuring that all steps of the transaction succeed or fail as a unit.

## two-phase commit

Two-phase commit is a protocol for ensuring all participants in a distributed transaction either commit or roll back the transaction, ensuring consistency across systems.
