Governed analytics, at near-zero cost
Tessallite answers the questions your business repeats every day — in Excel, Power BI, the API and the agent — from a tiny maintained summary instead of re-reading the whole terabyte. On a full terabyte of industry-standard data, that turns hundreds of dollars per thousand runs into a few cents, with the identical answer.
A question that costs hundreds of dollars to repeat runs for pennies.
Read from a maintained summary, not the whole terabyte.
Every accelerated answer matched the raw answer, exactly.
~$116,000 a year → ~$18 a year
A team running 40 dashboards refreshed hourly asks these questions roughly 350,000 times a year. Today that is about $116,000 in BigQuery scan; with Tessallite it is about $18 — the same answers, delivered to every tool. (BigQuery on-demand at ~$5/TB; per-run figures measured below.)
A real Excel workbook on this TPC-DS model. Opens with saved figures so you can explore offline; refreshing against the live model needs a Tessallite connection and credentials.
We asked each question through the live connection the way Excel or Power BI would — first the normal way (raw BigQuery), then with Tessallite — and the two answers came back identical. "Cost per 1,000 runs" uses BigQuery's on-demand price (~$5 per terabyte scanned, 10 MB minimum per query).
| Business question | Answered from | Data scanned today (raw BigQuery) | Data scanned with Tessallite | Cost per 1,000 runs (today → with Tessallite) | Same answer? |
|---|---|---|---|---|---|
| Sales revenue by year | maintained summary | 66.0 GB | 1,480 bytes | $330 → $0.05 | yes |
| Sales revenue by product category | maintained summary | 67.1 GB | 255 bytes | $335 → $0.05 | yes |
| Sales revenue by sales region | maintained summary | 66.0 GB | 41 bytes | $330 → $0.05 | yes |
| Sales revenue by customer type | maintained summary | 66.1 GB | 3,348 bytes | $330 → $0.05 | yes |
Tens of gigabytes the normal way; a few bytes with Tessallite — the same answer, for a fraction of a cent instead of a few hundred dollars per thousand runs. ("Customer type" is the retailer's preferred-customer flag.)
The cloud bill and the data each question moves, on a real linear scale — not compressed. Lower is better.
Three everyday questions, from a simple one to a heavy one. Red = today (raw BigQuery, each time); green = with Tessallite.
The green bars are a few cents — too small to see beside hundreds of dollars. That is the point.
The same three questions, in gigabytes. Red = raw BigQuery; green = with Tessallite.
The green bars are a few kilobytes to a few megabytes — invisible beside 66–155 GB. Same answer, tiny read.
Not one query — the everyday set a commercial, finance or merchandising team actually asks. For each, the data scanned the normal way versus with Tessallite, and the recurring cost at 1,000 runs.
| Business question | Data scanned today (raw BigQuery) | Data scanned with Tessallite | Cost per 1,000 runs (today → with Tessallite) |
|---|---|---|---|
| Sales revenue by region | 66.0 GB | 41 bytes | $330 → $0.05 |
| Sales revenue by quarter | 66.0 GB | 112 bytes | $330 → $0.05 |
| Sales revenue by product category | 67.1 GB | 255 bytes | $335 → $0.05 |
| Sales revenue by month | 66.0 GB | 304 bytes | $330 → $0.05 |
| Sales revenue by state | 66.0 GB | 436 bytes | $330 → $0.05 |
| Sales revenue by region, month by month | 88.0 GB | 725 bytes | $440 → $0.05 |
| Sales revenue by year and month | 66.0 GB | 2.0 KB | $330 → $0.05 |
| Sales revenue by product class | 67.1 GB | 2.6 KB | $335 → $0.05 |
| Sales revenue by product category, month by month | 89.1 GB | 4.4 KB | $445 → $0.05 |
| Sales revenue by customer type, month by month | 88.1 GB | 6.3 KB | $440 → $0.05 |
| Sales revenue by state, month by month | 88.0 GB | 7.8 KB | $440 → $0.05 |
| Sales revenue by product category, by year and month | 89.1 GB | 26.5 KB | $445 → $0.05 |
| Sales revenue by brand | 67.1 GB | 24.4 KB | $335 → $0.05 |
| Sales revenue by product category and brand | 67.1 GB | 47.7 KB | $335 → $0.05 |
| Sales revenue by region and state, month by month | 88.0 GB | 69.4 KB | $440 → $0.05 |
| Sales revenue by product category and brand, by quarter | 89.1 GB | 1.2 MB | $445 → $0.05 |
| Promotion impact: revenue by promotion type and category, month by month | 155.1 GB | 81.8 MB | $775 → $0.41 |
Two reusable governed lists — favourite product categories and key stores by state — are defined on the model so everyone filters on the same definition. The heaviest question in the set still drops from $775 to 41 cents per thousand runs.
The capabilities behind these results — and what your teams use day to day.
| Capability | What it does | What it did here |
|---|---|---|
| Governed semantic model | Business measures (revenue, margin, returns), dimensions (year, category, region, customer type) and the table joins are defined once, centrally. | "Revenue by category" means the same thing in Excel, the API and the agent — correct by design, not re-derived per tool. |
| Aggregate acceleration | Tessallite maintains small summaries of the huge fact table at the grains people actually query, and routes matching questions to them automatically. | The headline win: questions answered from byte- to kilobyte-sized summaries instead of scanning 66–155 GB — same answer, a fraction of the cost. |
| Transparent routing | For every query Tessallite records the route it chose, the bytes it scanned, and the summary it used. | That is how the numbers in this report were captured — straight from Tessallite's own log and the live run. |
| Multi-protocol gateway | One governed model served over SQL clients, Excel / Power BI, the REST API and the conversational agent. | The same accelerated answer reached every tool; these numbers came through the real connection a BI user uses. |
| Governed BigQuery source | A read-only, access-controlled connection to BigQuery; every query flows through the gateway. | BigQuery stays the engine and system of record — Tessallite adds governance and acceleration without copying data out. |
The industry's standard test, at full scale. TPC-DS is the benchmark the major data-platform vendors use to prove performance: a complete model of a real retailer — sales, returns, customers, promotions, calendar. We ran it at SF1000: a full terabyte, 2.88 billion sales records, 24 tables, loaded clean.
SF1000 — about one terabyte of analytics data.
2,879,987,999 line items — years of a large retailer's activity.
Stores, products, promotions, customers, dates — 0 load errors.
Model tpcds_retail_sf1000 · measured June 2026 · raw run records:
tpcds-sf1000-ab-postfix.json, tpcds-sf1000-bytes-matrix.json,
tpcds-sf1000-superset-matrix.json. TPC-DS-derived workload; not an official TPC audited result.