ClickHouse/docs/en/engines/table-engines/integrations/redis.md

---
slug: /en/engines/table-engines/integrations/redis
sidebar_position: 175
sidebar_label: Redis
---

# Redis

This engine allows integrating ClickHouse with [Redis](https://redis.io/). For Redis takes kv model, we strongly recommend you only query it in a point way, such as `where k=xx` or `where k in (xx, xx)`.

## Creating a Table {#creating-a-table}

``` sql
CREATE TABLE [IF NOT EXISTS] [db.]table_name
(
    name1 [type1],
    name2 [type2],
    ...
) ENGINE = Redis(host:port[, db_index[, password[, pool_size]]]) PRIMARY KEY(primary_key_name);
```

**Engine Parameters**

- `host:port` — Redis server address, you can ignore port and default Redis port 6379 will be used.

- `db_index` — Redis db index range from 0 to 15, default is 0.

- `password` — User password, default is blank string.

- `pool_size` — Redis max connection pool size, default is 16.

- `primary_key_name` - any column name in the column list.

- `primary` must be specified, it supports only one column in the primary key. The primary key will be serialized in binary as a Redis key.

- columns other than the primary key will be serialized in binary as Redis value in corresponding order.

- queries with key equals or in filtering will be optimized to multi keys lookup from Redis. If queries without filtering key full table scan will happen which is a heavy operation.

## Usage Example {#usage-example}

Create a table in ClickHouse which allows to read data from Redis:

``` sql
CREATE TABLE redis_table
(
    `key` String,
    `v1` UInt32,
    `v2` String,
    `v3` Float32
)
ENGINE = Redis('redis1:6379') PRIMARY KEY(key);
```

Insert:

```sql
INSERT INTO redis_table Values('1', 1, '1', 1.0), ('2', 2, '2', 2.0);
```

Query:

``` sql
SELECT COUNT(*) FROM redis_table;
```

``` text
┌─count()─┐
│       2 │
└─────────┘
```

``` sql
SELECT * FROM redis_table WHERE key='1';
```

```text
┌─key─┬─v1─┬─v2─┬─v3─┐
│ 1   │  1 │ 1  │  1 │
└─────┴────┴────┴────┘
```

``` sql
SELECT * FROM redis_table WHERE v1=2;
```

```text
┌─key─┬─v1─┬─v2─┬─v3─┐
│ 2   │  2 │ 2  │  2 │
└─────┴────┴────┴────┘
```

Update:

Note that the primary key cannot be updated.

```sql
ALTER TABLE redis_table UPDATE v1=2 WHERE key='1';
```

Delete:

```sql
ALTER TABLE redis_table DELETE WHERE key='1';
```

Truncate:

Flush Redis db asynchronously. Also `Truncate` support SYNC mode.

```sql
TRUNCATE TABLE redis_table SYNC;
```

Join:

Join with other tables.

```
SELECT * FROM redis_table JOIN merge_tree_table ON merge_tree_table.key=redis_table.key;
```

## Limitations {#limitations}

Redis engine also supports scanning queries, such as `where k > xx`, but it has some limitations:
1. Scanning query may produce some duplicated keys in a very rare case when it is rehashing. See details in [Redis Scan](https://github.com/redis/redis/blob/e4d183afd33e0b2e6e8d1c79a832f678a04a7886/src/dict.c#L1186-L1269).
2. During the scanning, keys could be created and deleted, so the resulting dataset can not represent a valid point in time.