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Syntasa

Product · Geospatial & Visualization

Query, index and map location data at scale.

Spatial SQL in every notebook from the moment Spark starts, hexagonal indexing with H3, and map dashboards your whole organization can read.

Talk with our teamSee notebooks

Three ways to look at location

Hexagons, regions and search within the map.

Each view pairs a map with the spatial SQL behind it, from hexagon density to regional roll-ups and drawn search areas.

Sample data
Notebook · spatial SQL
Result
FewerMore events
The libraries
H3, GeoMesa and Apache Sedona, included.
  • H3
    Hexagonal indexing at the resolution you choose. Libraries included in notebook and batch runtimes.
  • GeoMesa
    Spatial types and SQL functions registered automatically when Spark starts in a notebook.
  • Apache Sedona
    Spatial joins and functions at scale, in the notebook and batch runtime images on EMR, Dataproc and Azure.
How it works
Three steps from points to a picture.
  1. Step 1: Query
    Spatial SQL in notebooks: points, shapes, distance and containment.
  2. Step 2: Index
    Roll locations up into H3 hexagons for fast aggregation.
  3. Step 3: Map
    Show the result on interactive map dashboards.
Spatial SQL
Ready the moment Spark starts.
GeoMesa spatial types and functions are registered automatically in notebook Spark sessions, so you can write spatial SQL straight away, in Python or SQL cells.
  • Points, lines and polygons as column types
  • Containment, intersection and distance in SQL
  • Works on the same Delta tables as everything else
SQL cell · sample query
-- Count events per hexagon inside a region
SELECT h3_cell, count(*) AS events
FROM pings p JOIN regions r
  ON ST_Contains(r.geom, ST_Point(p.lon, p.lat))
GROUP BY h3_cell
Hexagonal indexing
Aggregate millions of points into hexagons.
Apache Sedona and H3 are included in the notebook and batch runtime images on EMR, Dataproc and Azure. Index locations into hexagons, then join, count and compare areas quickly.
  • Same libraries in notebooks and scheduled jobs
  • Hexagon grids at the resolution you choose
  • Results land in ordinary tables for dashboards
Map dashboards
Maps people actually read.
Dashboards are built in Apache Superset, embedded in Syntasa and themed to match.
  • deck.gl layers
    Points, hexagons, arcs and paths on interactive maps.
  • Country and world maps
    Choropleths by country or region.
  • MapBox
    Base maps and point layers.
  • OpenStreetMap heatmaps
    A Syntasa OpenStreetMap chart with heatmaps.
In disconnected sites, maps can use your own tile server.
Visualization and dashboards
From a chart in a notebook to a dashboard for everyone.
A wide chart library, Plotly Dash apps as a workflow step, and the no-code chart builder in every notebook. Your existing BI tools can read the same tables.
  • Line
  • Bar
  • Area
  • Scatter
  • Pie
  • Pivot tables
  • Tables
  • Heatmaps
  • Word clouds
  • Calendars
  • Maps
Bring your own BI: Tableau, Looker and Power BI connect to the tables.
Example uses
Where location changes the answer.
  • Mission analysis
    Patterns of movement and activity, aggregated by area, inside an accredited boundary.
    Learn more →
  • Public health access
    Where people need treatment, and how far it is. Arizona's treatment locator is one example.
    Learn more →
  • Retail catchments
    Regional demand and store catchments from first-party data.
    Learn more →
Put location data to work everywhere.
Map your own data with us.
Bring a location question and a sample dataset. We will query, index and map it together in a working session.
Talk with our teamExplore the platformA working session with our engineers, on your data and constraints.