---
title: Limitations
description: Caveats for aggregate support
canonical: https://docs.paradedb.com/documentation/aggregates/limitations
---

## ParadeDB Operator

In order for ParadeDB to push down an aggregate, a ParadeDB text search operator must be present in the query.

<CodeGroup>
```sql SQL
-- Not pushed down
SELECT COUNT(id) FROM mock_items
WHERE rating = 5;

-- Pushed down
SELECT COUNT(id) FROM mock_items
WHERE rating = 5
AND id @@@ pdb.all();
```

```python Django
from paradedb import All, ParadeDB

# Not pushed down — no ParadeDB operator
MockItem.objects.filter(rating=5).count()

# Pushed down — ParadeDB operator triggers aggregate pushdown
MockItem.objects.filter(rating=5, id=ParadeDB(All())).count()
```

```python SQLAlchemy
from sqlalchemy import func, select
from sqlalchemy.orm import Session
from paradedb.sqlalchemy import search

# Not pushed down.
count_without_operator_stmt = select(func.count(MockItem.id)).where(MockItem.rating == 5)

# Pushed down.
count_with_operator_stmt = select(func.count(MockItem.id)).where(
    MockItem.rating == 5,
    search.all(MockItem.id),
)

with Session(engine) as session:
    {
        "count_without_operator": session.execute(count_without_operator_stmt).scalar_one(),
        "count_with_operator": session.execute(count_with_operator_stmt).scalar_one(),
    }
```

```ruby Rails
# Not pushed down — no ParadeDB operator
MockItem.where(rating: 5).count

# Pushed down — ParadeDB operator triggers aggregate pushdown
MockItem.search(:id).match_all.where(rating: 5).count
```

</CodeGroup>

If your query does not contain a ParadeDB operator, a way to "force" aggregate pushdown is to append the [all query](/documentation/query-builder/compound/all) to the query's
`WHERE` clause.

## Join Support

Aggregate pushdown works across joins as well as single tables. When every participating table has a BM25 index and the custom aggregate scan is enabled, ParadeDB computes the result directly from the index's columnar storage, without scanning the underlying table rows.

```sql
SET paradedb.enable_aggregate_custom_scan TO on;
```

The following join shapes are supported:

| Feature | Supported |
| --- | --- |
| Join types | `INNER`, `LEFT`, `RIGHT`, `FULL OUTER` |
| Number of tables | Two or more (arbitrary join trees) |
| Aggregate functions | `COUNT`, `COUNT(DISTINCT ...)`, `SUM`, `SUM(DISTINCT ...)`, `AVG`, `AVG(DISTINCT ...)`, `MIN`, `MAX`, `STDDEV`, `STDDEV_POP`, `VARIANCE`, `VAR_POP`, `BOOL_AND`, `BOOL_OR`, `ARRAY_AGG`, `STRING_AGG` |
| `GROUP BY` | Columns from any table in the join, including JSON sub-fields via `metadata->>'key'` |
| `HAVING` clause | Comparisons against aggregate results and group columns |
| Per-aggregate `FILTER (WHERE ...)` | Yes |
| `ORDER BY ... LIMIT K` | Pushed down as TopK when there is a single `ORDER BY` column targeting an aggregate, a group column, or `MIN(col)` / `MAX(col)` |
| `ORDER BY` inside `STRING_AGG` / `ARRAY_AGG` | Yes (produces deterministic element ordering) |

ParadeDB falls back to native Postgres execution when any of the following are true:

- One or more tables in the join lacks a BM25 index
- The join has no equality join condition (e.g. `CROSS JOIN`)
- Join keys, `GROUP BY` columns, or aggregate arguments are not indexed columns
- The query uses window functions (`OVER ...`), `ROLLUP`, `CUBE`, `GROUPING SETS`, `LATERAL`, or `DISTINCT ON`
- `GROUP BY` uses a scalar function like `date_trunc(...)` or `lower(...)` (JSON sub-field access via `->>` is supported)
- The aggregate argument or result is wrapped in an expression such as `COALESCE(SUM(...), 0)` or a cast
- The query uses `pdb.agg()` (use standard SQL aggregate functions instead)

When a fallback happens, the query still runs correctly through Postgres' native planner. ParadeDB simply does not accelerate it.

<Note>
  Aggregate pushdown across joins is currently single-threaded. Parallel execution is on the [roadmap](/welcome/roadmap).
</Note>

## NUMERIC Columns

`NUMERIC` columns do not support aggregate pushdown. Queries with aggregates on `NUMERIC` columns will automatically fall back to PostgreSQL for aggregation.

For numeric data that requires aggregate pushdown, use `FLOAT` or `DOUBLE PRECISION` instead:

```sql
-- Aggregates can be pushed down
CREATE TABLE products (
    id SERIAL PRIMARY KEY,
    price DOUBLE PRECISION
);

-- Aggregates fall back to PostgreSQL
CREATE TABLE products (
    id SERIAL PRIMARY KEY,
    price NUMERIC(10,2)
);
```

<Note>
  Filter pushdown (equality and range queries) is fully supported for all
  `NUMERIC` columns. Only aggregate pushdown is not supported.
</Note>
