SingleStore Partner-Built In Dev
SingleStore is a distributed, cloud-native database that can handle transactional and analytical workloads with a unified engine. It provides real-time analytics, transactions, and streaming capabilities, enabling users to handle diverse workloads on a single platform.
Features
Feature Name | Supported | Notes |
---|---|---|
Capture deletes | check | |
History mode | ||
Custom data | ||
Data blocking | check | |
Column hashing | check | |
Re-sync | check | |
API configurable | check | |
Priority-first sync | ||
Fivetran data models | ||
Private networking | check | |
Authorization via API |
Setup guide
Follow our step-by-step SingleStore setup guide to connect SingleStore with your destination using Fivetran connectors.
Sync overview
Once Fivetran is connected to your SingleStore deployment, the connector fetches an initial consistent snapshot of all data from your SingleStore table. Once the initial sync is complete, the connector stream UPDATE/DELETE/INSERT events made to your SingleStore table.
SingleStore connector uses OBSERVE to capture change events.
Connector does not support handling schema changes. You cannot run ALTER
and DROP
queries while the OBSERVE
query is running.
Schema information
Fivetran replicates a single table of the SingleStore database. Selected SingleStore database is mapped to Fivetran schema.
Fivetran-generated columns
Fivetran adds the following columns to table in your destination:
_fivetran_deleted
(BOOLEAN) marks deleted rows in the source database._fivetran_synced
(UTC TIMESTAMP) indicates when Fivetran last successfully synced the row._fivetran_index
(INTEGER) shows the order of updates for tables that do not have a primary key._fivetran_id
(STRING) is the hash of the non-Fivetran values of each row. It's a unique ID that Fivetran uses to avoid duplicate rows in tables that do not have a primary key.
Type transformations and mapping
As we extract your data, we match SingleStore data types in your SingleStore database to types that Fivetran supports. If we don't support a specific data type, we automatically change that type to the closest supported type.
The following table illustrates how we transform your SingleStore data types into Fivetran supported types:
SingleStore Data Type | Fivetran Data Type | Notes |
---|---|---|
BOOL | SHORT | |
BIT | BINARY | |
TINYINT | SHORT | |
SMALLINT | SHORT | |
MEDIUMINT | INT | |
INT | INT | |
BIGINT | LONG | |
FLOAT | FLOAT | |
DOUBLE | DOUBLE | |
DECIMAL | DECIMAL | |
DATE | NAIVE_DATE | |
TIME | NAIVE_DATETIME | |
TIME(6) | NAIVE_DATETIME | |
DATETIME | NAIVE_DATETIME | |
DATETIME(6) | NAIVE_DATETIME | |
TIMESTAMP | NAIVE_DATETIME | |
TIMESTAMP(6) | NAIVE_DATETIME | |
YEAR | NAIVE_DATE | |
CHAR | STRING | |
VARCHAR | STRING | |
TINYTEXT | STRING | |
TEXT | STRING | |
MEDIUMTEXT | STRING | |
LONGTEXT | STRING | |
BINARY | BINARY | |
VARBINARY | BINARY | |
TINYBLOB | BINARY | |
BLOB | BINARY | |
MEDIUMBLOB | BINARY | |
LONGBLOB | BINARY | |
JSON | JSON | |
BSON | BINARY | |
GEOGRAPHY | STRING | |
GEOGRAPHYPOINT | STRING | |
ENUM | STRING | |
SET | STRING | |
VECTOR | BINARY/JSON | If the vector_type_project_format variable is set to BINARY , then VECTOR is mapped to BINARY . Otherwise, VEKTOR is mapped to JSON . |