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TileDB Open Source abstracts all the supported backends. It takes appropriate care to optimize IO for each backend using the corresponding SDK, and nicely abstracts the backends behind a virtual file system (VFS) class, so it is fairly easy for us to add new backend support in the future (e.g., NVMe) properly optimizing for it. Currently the following backends are supported (in addition to any POSIX local filesystem):
This is a simple guide that demonstrates how to use TileDB on Google Cloud Storage (GCS). After setting up TileDB to work with GCS, your TileDB programs will function properly without any API change! Instead of using local file system paths when creating/accessing groups, arrays, and VFS files: use URIs that start with gcs://
. For instance, if you wish to create (and subsequently write/read) an array on GCS, you use URI gcs://<your-bucket>/<your-array-name>
for the array name.
Navigate to the Google Cloud Console.
Create a service account.
Set your authentication environment variable.
The simplest option is to set the credentials path as an environment variable:
export GOOGLE_APPLICATION_CREDENTIALS=/path/to/gcs-creds.json
Configure your GCP project id by setting the following key in a configuration object (see Configuration):
TileDB will automatically authenticate using the configuration file referenced by the environment variable set in step 3. Bucket operations will be performed within the namespace of your configured project id.
So far we explained that TileDB arrays and groups are stored as directories. There is no directory concept on GCS and other similar object stores. However, GCS uses character /
in the object URIs which allows the same conceptual organization as a directory hierarchy in local storage. At a physical level, TileDB stores on GCS all the files it would create locally as objects. For instance, for array gcs://bucket/path/to/array
, TileDB creates array schema object gcs://bucket/path/to/array/__array_schema.tdb
, fragment metadata object gcs://bucket/path/to/array/<fragment>/__fragment_metadata.tdb
, and similarly all the other files/objects. Since there is no notion of a “directory” on GCS, nothing special is persisted on GCS for directories, e.g., gcs://bucket/path/to/array/<fragment>/
does not exist as an object.
TileDB writes the various fragment files as append-only objects using the insert object API of the Google Cloud C++ SDK. In addition to enabling appends, this API renders the TileDB writes to GCS particularly amenable to optimizations via parallelization. Since TileDB updates arrays only by writing (appending to) new files (i.e., it never updates a file in-place), TileDB does not need to download entire objects, update them, and re-upload them to GCS. This leads to excellent write performance.
TileDB reads utilize the range GET request API of the GCS SDK, which retrieves only the requested (contiguous) bytes from a file/object, rather than downloading the entire file from the cloud. This results in extremely fast subarray reads, especially because of the array tiling. Recall that a tile (which groups cell values that are stored contiguously in the file) is the atomic unit of IO. The range GET API enables reading each tile from GCS in a single request. Finally, TileDB performs all reads in parallel using multiple threads, which is a tunable configuration parameter.
While TileDB provides a native GCS backend implementation using the Google Cloud C++ SDK, it is also possible to use GCS via the GCS-S3 compatibility API using our S3 backend. Doing so requires setting several configuration parameters:
Note: vfs.s3.use_multipart_upload=true
may work with recent GCS updates, but has not yet been tested/evaluated by TileDB.
Full example for GCS via S3 compatibility in Python:
If you have already:
saved your AWS credentials using the AWS CLI aws login
command
installed TileDB-Py with pip install tiledb
or mamba install -c conda-forge tiledb-py
Then the following should work for any bucket in the us-east-1
region:
If the bucket is in another region, then use:
This is a simple guide that demonstrates how to use TileDB on AWS S3. After configuring TileDB to work with AWS S3, your TileDB programs will function properly without any API change! Instead of using local file system paths for referencing files (e.g. arrays, groups, VFS files) use must format your URIs to start with s3://
. For instance, if you wish to create (and subsequently write/read) an array on AWS S3, you use URI s3://<your-bucket>/<your-array-name>
for the array name.
First, we need to set up an AWS account and generate access keys.
Create a new AWS account.
Visit the AWS console and sign in.
On the AWS console, click on the Services
drop-down menu and select Storage->S3
. You can create S3 buckets there.
On the AWS console, click on the Services
drop-down menu and select Security, Identity & Compliance->IAM
.
Click on Users
from the left-hand side menu, and then click on the Add User
button. Provide the email or username of the user you wish to add, select the Programmatic Access
checkbox and click on Next: Permissions
.
Click on the Attach existing policies directly
button, search for the S3-related policies and add the policy of your choice (e.g., full-access, read-only, etc.). Click on Next
and then Create User
.
Using TileDB with an existing bucket requires at least the following S3 permissions:
Upon successful creation, the next page will show the user along with two keys: Access key ID
and Secret access key
. Write down both these keys.
There are multiple supported ways to access resources on AWS. You can either request access with long-term access credentials (e.g. Access Keys) or temporary ones by utilizing AWS Security Token Service.
Access keys are long-term credentials for an IAM user or the AWS account root user. To be able to access AWS resource this way you need to follow the next steps:
1. Export these keys to your environment from a console:
2. Or, set the following keys in a configuration object (see Configuration):
TileDB (version 1.8+
) supports authentication with temporary credentials from the AWS Session Token. This method of acquiring temporary credentials is preferred in case you want to maintain permissions solely within your organization
TileDB (version 2.1+
) supports authentication with temporary credentials from the AWS Assume Role. If you prefer to maintain permissions within AWS, this method's base permissions for the temporary credentials will be derived from the policy on a role. You can use them to access AWS resources, that you might not normally have access to. In this case you will need to configure the following:
Using this method, the IAM
user credentials used by your proxy server only requires the ability to call sts:AssumeRole
. There is one extra step of creating a new role and attaching trust policy to it, which is not the case with Session Tokens approach.
Now you are ready to start writing TileDB programs! When creating a TileDB context or a VFS object, you need to set up a configuration object with the following parameters for AWS S3 (supposing that your S3 buckets are on region us-east-
- you can set an arbitrary region).
The above configuration parameters are currently set as shown in TileDB by default. However, we suggest to always check whether the default values are the desired ones for your application.
So far we explained that TileDB arrays and groups are stored as directories. There is no directory concept on S3 and other similar object stores. However, S3 uses character /
in the object URIs which allows the same conceptual organization as a directory hierarchy in local storage. At a physical level, TileDB stores on S3 all the files it would create locally as objects. For instance, for array s3://bucket/path/to/array
, TileDB creates array schema object s3://bucket/path/to/array/__array_schema.tdb
, fragment metadata object s3://bucket/path/to/array/<fragment>/__fragment_metadata.tdb
, and similarly all the other files/objects. Since there is no notion of a “directory” on S3, nothing special is persisted on S3 for directories, e.g., s3://bucket/path/to/array/<fragment>/
does not exist as an object.
The AWS S3 CLI allows you to sync (i.e., download) the S3 objects having a common URI prefix to local storage, organizing them into a directory hierarchy based on the use of /
in the object URIs. This makes it very easy to clone TileDB arrays or entire groups locally from S3. For instance, given an array my_array
you created and wrote on an S3 bucket my_bucket
, you can clone it locally to an array my_local_array
with the following command from your console:
After downloading an array locally, your TileDB program will function properly by changing the array name from s3://my_bucket/my_array
to my_local_array
, without any other modification.
TileDB writes the various fragment files as append-only objects using the multi-part upload API of the AWS C++ SDK. In addition to enabling appends, this API renders the TileDB writes to S3 particularly amenable to optimizations via parallelization. Since TileDB updates arrays only by writing (appending to) new files (i.e., it never updates a file in-place), TileDB does not need to download entire objects, update them, and re-upload them to S3. This leads to excellent write performance.
TileDB reads utilize the range GET request API of the AWS SDK, which retrieves only the requested (contiguous) bytes from a file/object, rather than downloading the entire file from the cloud. This results in extremely fast subarray reads, especially because of the array tiling. Recall that a tile (which groups cell values that are stored contiguously in the file) is the atomic unit of IO. The range GET API enables reading each tile from S3 in a single request. Finally, TileDB performs all reads in parallel using multiple threads, which is a tunable configuration parameter.
The AWS backend supports several settings for proxy servers:
It is necessary to override "vfs.s3.proxy_scheme" to `http`
for most proxy setups. TileDB currently 2.0.8 uses the default setting, which will be updated in the next release.
TileDB uses the AWS C++ SDK and cURL for access to S3. The AWS SDK logging level is a process-global setting. The configuration of the most recently constructed context will set the process state. Log files are written to the process working directory.
TileDB uses the AWS C++ SDK and cURL for access to S3. The AWS SDK logging level is a process-global setting. The configuration of the most recently constructed context will set the process state. Log files are written to the process working directory.
There is no universal location for SSL/TLS certificates on Linux. While TileDB searches for the default CA store on several major distributions, other systems or custom certificates may require path specification. to SSL/TLS certificate file to be used by cURL for for S3 HTTPS encryption. These parameters follow cURL conventions: https://curl.haxx.se/docs/manpage.html
For debugging purposes only it is possible to disable SSL/TLS certificate verification:
Lustre supports POSIX file locking semantics and exposes local- (mount with -o localflock
) and cluster- (mount with -o flock
) level locking.
The HDFS backend currently only works on POSIX (Linux, macOS) platforms. Windows is currently not supported.
TileDB integrates with HDFS through the libhdfs
library (HDFS C-API). The HDFS backend is enabled by default and libhdfs
loading happens at runtime based on environment variables:
If the library cannot be found, or if the Hadoop library cannot locate the correct library dependencies a runtime, an error will be returned.
To use HDFS with TileDB, change the URI you use to an HDFS path:
hdfs://<authority>:<port>/path/to/array
For instance, if you are running a local HDFS namenode on port 9000:
hdfs://localhost:9000/path/to/array
If you want to use the namenode specified in your HDFS configuration files, then change the prefix to:
hdfs:///path/to/array
or hdfs://default/path/to/array
Most HDFS configuration variables are defined in Hadoop specific XML files. TileDB allows the following configuration variables to be set at run time through configuration parameters:
This is a simple guide that demonstrates how to use TileDB on Azure Blob Storage. After configuring TileDB to work with Azure, your TileDB programs will function properly without any API change! Instead of using local file system paths for referencing files (e.g. arrays, groups, VFS files) use must format your URIs to start with azure://
. For instance, if you wish to create (and subsequently write and read) an array on Azure, you use a URI of the format azure://<storage-container>/<your-array-name>
for the array name.
Sign into the Azure portal, create a new account if necessary.
On the Azure portal, click on the Storage accounts
service.
Select the +Add
button to navigate to the Create a storage account
form.
Complete the form and create the storage account. You may use a Standard or Premium Block Blob account type.
TileDB supports authenticating to Azure through Microsoft Entra ID, access keys and shared access signature tokens.
Only system-assigned managed identities are currently supported.
When the Azure backend gets initialized, it attempts to obtain credentials by the sources above. If no credentials can be obtained, TileDB will fall back to anonymous authentication.
Microsoft Entra ID will not be used if one of the following conditions apply:
One of the authentication methods below is specified.
Once your storage account has been created, navigate to its landing page. From the left menu, select the Access keys
option. Copy the Storage account name
and one of the auto-generated Key
s.
Navigate to the new storage account landing page. From the left menu, select the “Shared Access Signature” option.
Use all checked defaults, and select Allowed resource types
→ Container
Set an appropriate expiration date (note: SAS tokens cannot be revoked)
Click Generate SAS and connection string
Copy the SAS Token
(second entry) and use in the TileDB config:
So far we explained that TileDB arrays and groups are stored as directories. There is no directory concept on Azure Blob Storage (similar to other popular object stores). However, Azure uses character /
in the object URIs which allows the same conceptual organization as a directory hierarchy in local storage. At a physical level, TileDB stores all files on Azure that it would create locally as objects. For instance, for array azure://container/path/to/array
, TileDB creates array schema object azure://container/path/to/array/__array_schema.tdb
, fragment metadata object azure://container/path/to/array/<fragment>/__fragment_metadata.tdb
, and similarly all the other files/objects. Since there is no notion of a “directory” on Azure, nothing special is persisted on Azure for directories, e.g., azure://container/path/to/array/<fragment>/
does not exist as an object.
TileDB reads utilize the range GET blob request API of the Azure SDK, which retrieves only the requested (contiguous) bytes from a file/object, rather than downloading the entire file from the cloud. This results in extremely fast subarray reads, especially because of the array tiling. Recall that a tile (which groups cell values that are stored contiguously in the file) is the atomic unit of IO. The range GET API enables reading each tile from Azure in a single request. Finally, TileDB performs all reads in parallel using multiple threads, which is a tunable configuration parameter.
By default, the blob endpoint will be set to https://foo.blob.core.windows.net
, where foo
is the storage account name. You can use the "vfs.azure.blob_endpoint"
config parameter to override the default blob endpoint.
If the custom endpoint contains a SAS token, the "vfs.azure.storage_sas_token"
option must not be specified.
Once you get MinIO server running, you need to set the S3 configurations as follows (below, <port>
stands for the port on which you are running the MinIO server, equal to 9999
if you run the MinIO docker as shown above):
Config option | GCS setting |
---|---|
is a POSIX-compliant distributed filesystem and, therefore, TileDB "just works" on Lustre. Care must be taken to enable file locking for process-safety during consolidation (see for more details).
This is a simple guide that demonstrates how to use TileDB on . HDFS is a distributed Java-based filesystem for storing large amounts of data. It is the underlying distributed storage layer for the Hadoop stack.
Env variable | Description |
---|
Parameter | Description |
---|
The page explains how to set configuration parameters in TileDB.
TileDB does not support .
Microsoft Entra ID is and provides superior security and fine-grained access compared to shared keys. It is enabled by default and you do not need to specifically configure TileDB to use it. Credentials are obtained automatically from the following sources in order:
for Azure compute resources
for Kubernetes
A is specified that is not using HTTPS.
Make sure to assign the right roles to the identity to use with TileDB. The general and roles do not provide access to data inside the storage accounts. You need to assign the or the roles in order to read or write data respectively.
Authentication with shared keys is considered insecure. You are recommended to use .
Set the following keys in a configuration object (see ). Use the storage account name and key from the last step.
Parameter | Default Value |
---|
Parameter | Default Value |
---|
TileDB writes the various fragment files as append-only objects using the block-list upload API of the . In addition to enabling appends, this API renders the TileDB writes to Azure particularly amenable to optimizations via parallelization. Since TileDB updates arrays only by writing (appending to) new files (i.e., it never updates a file in-place), TileDB does not need to download entire objects, update them, and re-upload them to Azure. This leads to excellent write performance.
Parameter | Default Value |
---|
is a lightweight S3-compliant object-store. Although it has many nice features, here we focus only on local deployment, which is very useful if you wish to quickly test your TileDB-S3 programs locally. See the for installation instructions. Here is what we do to run MinIO on port 9999
:
The page explains in detail how to set configuration parameters in TileDB. Below is a quick example for the minio specific parameters.
Parameter
Default Value
"vfs.gcs.project_id"
""
"vfs.s3.endpoint_override"
"storage.googleapis.com"
"vfs.s3.region"
"auto"
"vfs.s3.use_multipart_upload"
"false"
"vfs.s3.aws_access_key_id"
, "vfs.s3.aws_secret_access_key"
Override here, or set as usual using AWS settings or environment variables.
Parameter
Default Value
"vfs.s3.aws_access_key_id"
""
"vfs.s3.aws_secret_access_key"
""
Parameter
Values
"vfs.s3.aws_session_token"
(session token corresponding to the configured key/secret pair)
Parameter
Default Value
"vfs.s3.aws_role_arn"
Required - (The Amazon Resource Name (ARN) of the role to assume)
"vfs.s3.aws_session_name"
Optional - (An identifier for the assumed role session)
"vfs.s3.aws_external_id"
Optional - (A unique identifier that might be required when you assume a role in another account)
"vfs.s3.aws_load_freq"
Optional - (The duration, in minutes, of the role session)
Parameter
Value
"vfs.s3.scheme"
"https"
"vfs.s3.region"
"us-east-1"
"vfs.s3.endpoint_override"
""
"vfs.s3.use_virtual_addressing"
"true"
Parameter
Default
Description
"vfs.s3.proxy_host"
""
The S3 proxy host.
"vfs.s3.proxy_port"
"0"
The S3 proxy port.
"vfs.s3.proxy_scheme"
"https"
The S3 proxy scheme.
"vfs.s3.proxy_username"
""
The S3 proxy username.
"vfs.s3.proxy_password"
""
The S3 proxy password.
Parameter
Values
"vfs.s3.logging_level"
[OFF], TRACE, DEBUG
Parameter
Value
"vfs.s3.ca_file"
[file path]
"vfs.s3.ca_path"
[directory path]
Parameter
Default
"vfs.s3.verify_ssl"
[false], true
| The root of your installed Hadoop distribution. TileDB will search the path |
| The location of the Java SDK installation. The |
| The Java classpath including the Hadoop jar files. The correct |
| Optional runtime username to use when connecting to the HDFS cluster. |
| Optional namenode URI to use (TileDB will use |
| Path to the Kerberos ticket cache when connecting to an HDFS cluster. |
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