Data Sources
Dremio supports a variety of data sources, including NoSQL databases, relational databases, Hadoop, local filesystems, and cloud storage.
IMPORTANT
Case-sensitive source data file/table names are not supported.
In Dremio, data filenames in your data source are “seen” in a case-insensitive manner. So, if you have to three (3) file names with difference cases (for example,
JOE
Joe
, andjoe
), Dremio “sees” the files as having the same name. Thus, searching onJoe
,JOE
, orjoe
, can result in unanticipated data results.In addition, column names within a table that have the same name with different cases are not supported. For example, if two (2) columns named
Trip_Pickup_DateTime
andtrip_pickup_datetime
exist in the table, one of the columns may disappear when the header is extracted.
Files and Directories
Relational databases
- Amazon Redshift
- Azure Data Explorer
- IBM DB2 (Not Supported)
- Microsoft SQL Server
- MySQL
- Oracle
- Postgres
- Teradata (Beta)
Dremio enables users to run external queries, queries that use the native syntax of the relational database, to process SQL statements that are not yet supported by Dremio or are too complex to convert. Dremio administrators enable the feature for each data source and specify which Dremio users can edit that source. See External Queries for more information.
Dremio improves query performance for relational database datasets with Runtime Filtering, which applies dimension table filters to joined fact tables at runtime.
Note:
Decimal Support
As of Dremio 4.0, decimal-to-decimal mappings are supported for relational database sources.
CollationRelational database sources must have a collation equivalent to
LATIN1_GENERAL_BIN2
to ensure consistent results when operations are pushed down. For non-equivalent collations, create a view that coerces the collation to one that is equivalent toLATIN1_GENERAL_BIN2
and access that view.