Glossary

The task of collecting a set of values to return a single value. When data is aggregated, data rows are replaced with totals or summary statistics.

A node that routes queries to the leaf nodes, aggregates intermediate results, and sends the results back to a client. There are two types of aggregators: master and child.

An algorithm used by SingleStoreDB that allows columnstore segments to maintain sort order (as close as possible), while data is being ingested or updated

A node that can be promoted to the role of Master Aggregator in the event that the existing Master Aggregator’s host fails. Depending on the query volume, a workspace may contain zero or more child aggregators.

An industrial compiler to produce highly efficient machine code that enables low-level optimizations, which are not possible when executing queries via interpretation alone. By default, queries are interpreted first and then asynchronously compiled in the background for use in later executions. This speeds up query execution time for long and complex queries, while at the same time providing efficient query plans for later use.

A named temporary result set that exists within the scope of a single statement and that can be referred to later within that statement, possibly multiple times.

A user that resides in the workspace. A database user’s lifetime is bound to that workspace such that, when a workspace is terminated, all of the users, permissions, and groups are permanently removed as well. Database users can connect to a workspace via SQL client and run SQL queries against their data. Unlike organization users, database users must be managed via SQL statements.

A situation when two or more transactions mutually hold and request a table write that the other transaction needs.

Globbing is commonly used in data ingest to read or select a subset of files based on a naming pattern. Data ingest uses globbing to process large numbers of files quickly and efficiently, especially when the file names follow a predictable naming pattern.

A distributed file system by Apache Hadoop. It is highly fault tolerant and designed to run on COTS (Commercial Off the Shelf) or low cost out-of-the-box hardware.

A data structure optimized for fast equality lookups by a key.

A set of data items that are related to each other by hierarchical relationships. Hierarchical relationships exist where one item of data is the parent of another item(s).

A hardware or virtual machine which holds the aggregator and leaf nodes that comprise a SingleStoreDB Cloud workspace.

Holds the information or metadata for all the databases in a workspace.

A SELECT statement embedded in the FROM or WITH clause of another SELECT statement that creates a temporary table that is operated on by the outer query.

An in-place change in a database refers to modifying the data or schema of the database without requiring a full data migration or recreation of the database. It allows you to make changes to the database while minimizing downtime and preserving existing data.

An open standard file format and data interchange format that uses human-readable text to store and transmit data objects consisting of attribute–value pairs and arrays.

A set of keys containing public keys that can be used to authenticate any JWT.

An open, industry standard typically used for authorization and information exchange.

A node that stores a subset of a workspace’s data. A leaf node functions as a storage and compute node. To optimize performance, SingleStoreDB automatically distributes data across leaf nodes into partitions. Each leaf node contains several partitions.

A specialized node that’s responsible for workspace monitoring and failover. It orchestrates basic workspace operations and all DDL operations.

Information about a database's schema, access to the database, storage, built-in programs, and or other information about the data such as date created, file size, and etc.

A SingleStoreDB server. A host may contain one or more SingleStoreDB server instances.

A computer memory design used in multiprocessing. Through NUMA, a processor can access memory that’s considered “local memory” faster than it can access memory that is local to another processor, or memory that is shared between processors.

Organizing data to appear similar across all records and fields.

A data storage architecture that manages data as objects, as opposed to other storage architectures like file systems which manages data as a file hierarchy, and block storage which manages data as blocks within sectors and tracks.

A data processing type that is designed to analyze data dimensions concurrently.

A data processing type that executes a number of transactions occurring concurrently.

Allows shared access to workspaces and related resources within a company or group.

An organization user resides within the “control plane” of SingleStoreDB Cloud and can perform those actions that are available on the Cloud Portal, such as manage organization users, manage workspaces, and run SQL queries against workspace data via the Cloud Portal SQL editor.

A partition contains a subset (a shard) of a database’s data. Each partition holds a vertical slice of data, distributed as per a hashing algorithm on the primary key or randomly for keyless sharded databases.

Persisting the name of a file is storing the file name so it can be retrieved and used again later in a program or system.

A feature that continuously loads data as it arrives from external sources. As a built-in component of the database, Pipelines can extract, shape (modify), and load external data without the need for third-party tools or middleware.

An application that allows you to design, manage, and monitor your SingleStoreDB Cloud instances.

A user that can log into the Cloud Portal and access portal services. Each Cloud Portal user is associated with a default organization and automatically has access to all of the workspaces and related resources within it.

Patterns or structures in query. Some query shapes are unsupported in SingleStoreDB.

A computer's short-term memory. It is where the data that the processor is currently using is stored temporarily. RAM can be accessed much faster than data on a hard disk, solid-state disk, or another long-term storage device, which is why RAM capacity is so important for system performance.

Ensures redundancy in a cluster. There are two types of replication: high availability - replicating partitions between the leaf nodes and cluster replication - replicating partitions between clusters.

A process where metadata stored for columnstore segments is used to determine where a segment can match a filter queried at execution time.

An isolation level provides the strictest transaction isolation. This level guarantees transactions that are executed in parallel produce the same result as if they were executed serially (one at a time).

A subset of a databases's data.

A solid-state drive is a storage device. It is a non-volatile medium that stores persistent data on solid-state flash memory.

Single sign-on, where one can log into SingleStoreDB Cloud via Azure AD, Okta, and PingOne.

A data structure optimized for ordered data that allows for queries to quickly seek data by binary searching.

The amount of components installed and or configuration options that are enabled.

A type of database partitioning that divides a database into smaller more easily manageable parts.

SingleStoreDB Cloud’s version of a cluster.

A collection of SingleStoreDB aggregator and leaf nodes.