Chore: Wording -- use time series database

Author: amotl

doc/source/about/technologies.rst

@@ -26,12 +26,12 @@ Infrastructure components
 
 - Kotori_, a data acquisition, graphing and telemetry toolkit
 - Grafana_, a graph and dashboard builder for visualizing time series metrics
-- CrateDB_, a time-series database ¹
-- InfluxDB_, a time-series database ¹
+- CrateDB_, a time series database with document features and more ¹
+- InfluxDB_, a time series database ¹
 - Mosquitto_, an MQTT message broker
 - MongoDB_, a document store (optional) ²³
 
-| ¹ Kotori can either use CrateDB or InfluxDB as timeseries database.
+| ¹ Kotori can either use CrateDB or InfluxDB as time series database.
 | ² MongoDB is only required when doing CSV data acquisition, so it is completely
 | optional for regular operations of Kotori.
 | ³ As MongoDB - strictly speaking - stopped being free software recently (2018/2019),

doc/source/attic/setup/debian-amd64.rst

@@ -16,7 +16,7 @@ Intro
 Install the whole stack on a Debian-based system. It is currently made of these free and open source software components:
 
 - Mosquitto_, a MQTT message broker
-- InfluxDB_, a time-series database
+- InfluxDB_, a time series database
 - Grafana_, a graph and dashboard builder for visualizing time series metrics
 - :ref:`Kotori`, a data acquisition, graphing and telemetry toolkit
 

doc/source/database/cratedb.rst

@@ -25,7 +25,7 @@ This section summarizes CrateDB's data model and query interface.
 Data model
 ==========
 
-As a time-series/document/OLAP/RDBMS database with an SQL interface, CrateDB stores records
+As a timeseries/document/OLAP/RDBMS database with an SQL interface, CrateDB stores records
 into tables. Tables are grouped into schemas, which is equivalent to the concept of hosting
 multiple databases on the same server instance.
 
@@ -71,7 +71,7 @@ At a glance
 - Use standard SQL via the PostgreSQL wire protocol or an HTTP API.
 - Dynamic table schemas and queryable objects provide document-oriented features in
   addition to the relational features of SQL.
-- Support for time-series data, realtime full-text search, geospatial data types and
+- Support for time series data, realtime full-text search, geospatial data types and
   search capabilities.
 - Horizontally scalable, highly available and fault tolerant clusters that run very
   well in virtualized and containerised environments.
@@ -315,7 +315,7 @@ Typical queries
 Advanced queries
 ================
 
-Time-series data
+Time series data
 ----------------
 
 .. code-block:: sql
@@ -520,7 +520,7 @@ Usage
 Purpose
 =======
 
-Kotori uses CrateDB to store **timeseries-data** of data acquisition channels.
+Kotori uses CrateDB to store time series data of data acquisition channels.
 
 Documentation
 =============

doc/source/database/index.md

@@ -3,7 +3,7 @@
 # Databases
 
 Database adapter components will know about vendor-specific dialects and optimal
-communication strategies to timeseries-databases.
+communication strategies to time series databases.
 
 This documentation section enumerates the collection of database adapters shipped
 with Kotori. Adding more adapters is possible.
@@ -39,7 +39,7 @@ amounts of data in near real-time, even with complex queries. It is PostgreSQL-c
 and based on Lucene.
 
 <small>
-<strong>Categories:</strong> timeseries-database, multi-modal database
+<strong>Categories:</strong> time series database, multi-modal database
 </small>
 :::
 :::{grid-item}
@@ -68,7 +68,7 @@ and real-time analytics. It covers storing and querying data, background ETL pro
 for monitoring and alerting purposes, and visualization and exploration features. 
 
 <small>
-<strong>Categories:</strong> timeseries-database
+<strong>Categories:</strong> time series database
 </small>
 :::
 :::{grid-item}

doc/source/setup/docker.rst

@@ -97,7 +97,7 @@ telemetry message bus to the database.
 CrateDB
 =======
 
-This example uses CrateDB as timeseries-database.
+This example uses CrateDB as time series database.
 
 Invoke Kotori::
 
@@ -125,7 +125,7 @@ Go to Grafana and visit the dashboard just created::
 InfluxDB
 ========
 
-This example uses InfluxDB as timeseries-database.
+This example uses InfluxDB as time series database.
 
 Invoke Kotori::
 

kotori/daq/graphing/grafana/manager.py

@@ -31,7 +31,7 @@ def __init__(self, settings=None, channel=None):
         elif "influxdb" in self.config:
             self.dbtype = TimeseriesDatabaseType.INFLUXDB1
         else:
-            raise ValueError("Timeseries database type not defined")
+            raise ValueError("Time series database type not defined")
 
         if not 'port' in self.config['grafana']:
             self.config['grafana']['port'] = '3000'
@@ -110,7 +110,7 @@ def create_datasource(self, storage_location):
                 "password": self.config['influxdb']['password'],
             })
         else:
-            log.warn("No time-series database enabled, skipping Grafana provisioning")
+            log.warn("No time series database enabled, skipping Grafana provisioning")
 
 
         return datasource_name

kotori/daq/services/mig.py

@@ -88,7 +88,7 @@ def setupService(self):
         elif "cratedb" in self.settings:
             self.database = CrateDBAdapter(settings = self.settings.cratedb)
         else:
-            log.warn("No time-series database configured")
+            log.warn("No time series database configured")
 
         # Perform MQTT message processing using a different thread pool
         self.threadpool = ThreadPool()
@@ -315,7 +315,7 @@ def emit_message(self, message):
 
     def store_message(self, storage, data):
         """
-        Store data to timeseries database
+        Store data to time series database
 
         :param storage: The storage location object
         :param data:    The data ready for storing

kotori/io/export/database.py

@@ -37,7 +37,7 @@ def query(self):
                 settings=self.settings.cratedb,
             )
         else:
-            log.warn("No time-series database configured")
+            log.warn("No time series database configured")
             return
 
         # Get query expression from transformation dictionary.

test/test_export.py

@@ -34,7 +34,7 @@ def test_export_cratedb_general(machinery_cratedb, reset_cratedb):
     Submit single reading in JSON format to HTTP API and proof
     it can be retrieved back from the HTTP API in different formats.
 
-    This uses CrateDB as timeseries database.
+    This uses CrateDB as time series database.
     """
 
     channel_path = settings.io_channel_path
@@ -53,7 +53,7 @@ def test_export_influxdb_general(machinery, create_influxdb, reset_influxdb):
     Submit single reading in JSON format to HTTP API and proof
     it can be retrieved back from the HTTP API in different formats.
 
-    This uses InfluxDB as timeseries database.
+    This uses InfluxDB as time series database.
     """
 
     channel_path = settings.channel_path_data