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Glossary

This page lists key terms and concepts in Timeplus.

bookmark

Query bookmark. You can save the common SQL statements as bookmarks. They can be run quickly in the web console by a single click. You can create, list, edit, remove bookmarks in the query page.

Both bookmarks and views can help you easiliy re-run a query. However views are defined in the streaming database and you can query the view directly via select .. from .. But bookmarks are just UI shortcuts. When you click the bookmark, the original SQL statement will be pre-filled in the query console. You cannot run select .. from my_bookmark

dashboard

You can add one or more panels in a dashboard. You can also create one or more dashboards in a workspace.

event time

Event time is used to identify when the event is generated, like a birthday to a human being. It can be the exact timestamp when the order is placed, when the user logins a system, when an error occurs, or when a IoT device reports its status. If no suitable timestamp attribute in the event, Timeplus will generate the event time based on the data ingestion time.

Learn more: Event time

generator

Timeplus ships a streaming data generator to help you quickly load sample data into the system. Three typeical streaming data types are provided: iot_data, user_logins, devlops.

Learn more Streaming Generator

materialized view

A special view that is kept running in the background and persistent the query results in an internal stream.

query

Timeplus provides powerful streaming analyatics capabilities through the enhanced SQL. By default, queries are unbounded and keeps pushing latest results to the client. The unbounded query can be converted to a bounded query by applying the function table(), when the user wants to ask the question about what has happened like the traditional SQL.

Learn more: Streaming Query and Non-Streaming Query

sink

a.k.a. destination.

Timeplus enables you to send real-time insights to other systems, either to notify individuals or power up downstream applications.

Learn more: Destination.

source

A source is a background job in Timeplus to load data into a stream. Timeplus integrates with a wide range of systems as data sources, such as Apache Kafka.

Learn more: Data Ingestion

stream

Timeplus is a streaming analytics platform and data lives in streams. Timeplus streams are similar to tables in the traditional SQL databases. Both of them are essentially dataset. The key difference is that Timeplus stream is an append-only, unbounded, constantly changing events group.

Learn more: Stream

timestamp column

When you create a source and preview the data, you can choose a column as the timestamp column. Timeplus will use this column as the event time and track the lifecycle of the event and process it for all time related computation/aggregation.

view

You can define reusable SQL statements as views, so that you can query them as if they are streams select .. from view1 .. By default, views don't take any extra computing or stroage resource. They are expected to the SQL definition when they are queried. You can also create materialized views to 'materialize' them (keeping running them in the background and saving the results to the disk)

Learn more: View and Materialized View

workspace

A workspace is the isolated storage and computing unit for you to run streaming data collection and analysis. During the beta program, every user can create up to 1 free workspace and join many workspaces. Usually a group of users in the same organization join the same workspace, to build one or more streaming analytics solutions.

By default, each workspace can save up to 50GB data and with a limit for concurrent queries. If you need more resource, please contact eng@timeplus.io to increaes the limit