Amazon Neptune Engine Version (2021-06-01) - Amazon Neptune
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Amazon Neptune Engine Version (2021-06-01)

As of 2021-06-01, engine version is being generally deployed. Please note that it takes several days for a new release to become available in every region.

Subsequent Patch Releases for This Release

Known issues in this engine release


A SPARQL bug that fails to honor media type in an Accept header if there are spaces present.

For example, a query with -H "Accept: text/csv; q=1.0, */*; q=0.1" returns JSON output rather than CSV output.


If you remove the spaces in the Accept clause in the header, the engine returns output in the correct requested format. In other words, instead of -H "Accept: text/csv; q=1.0, */*; q=0.1" , use:

-H "Accept: text/csv;q=1.0,*/*;q=0.1"

New Features in This Engine Release

  • Added the new R5d instance type, which includes a lookup cache for speeding up reads in use cases involving a high volume of property value or RDF literal lookups. See The Neptune lookup cache can accelerate read queries.

  • Added a new lab-mode parameter that lets the experimental DFE engine be invoked only on a per-query basis with the useDFE query hint.

Improvements in This Engine Release

  • Added support for TinkerPop 3.4.10.

  • Added support for using the withStrategies( ) configuration step when sending Gremlin script requests. Specifically, the SubgraphStrategy, PartitionStrategy, ReadOnlyStrategy, EdgeLabelVerificationStrategy, and ReservedKeysVerificationStrategy are all supported.

  • Added optimization for V() traversals in the middle of a query. Previously, such traversals were not optimized in Neptune.

  • Added support for RFC 2141 URNs to be used as the baseUri and namedGraphUri parameters for a bulk load.

Defects Fixed in This Engine Release

  • Fixed a Gremlin bug in the parser where incorrect queries were treated as valid.

  • Fixed a Gremlin bug where unfolding an aggregate() side-effect with cap().unfold() to a valueMap() would raise an exception.

  • Fixed a Gremlin bug where some property() steps after an addV() step fail with a "cannot cast to String" error.

  • Fixed a Gremlin bug to prevent some conditional insert patterns from raising concurrent-modification exceptions.

  • Fixed a Gremlin bug so that the query request timeout now cannot exceed the session timeout.

  • Fixed a SPARQL bug where updates using LOAD or UNLOAD could fail with an HTTP code 500 instead of HTTP code 400 when the remote server is unavailable.

  • Fixed a bug where stream API calls were failing when commitNum or opNum values larger than the 32-bit signed integer limit (2,147,483,647) were used.

Query-Language Versions Supported in This Release

Before upgrading a DB cluster to version, make sure that your project is compatible with these query-language versions:

  • Gremlin version: 3.4.10

  • SPARQL version: 1.1

Upgrade Paths to Engine Release

You can manually upgrade any previous Neptune engine release to this release.

You will not automatically upgrade to this release.

Upgrading to This Release

Amazon Neptune is now generally available.

If a DB cluster is running an engine version from which there is an upgrade path to this release, it is eligible to be upgraded now. You can upgrade any eligible cluster using the DB cluster operations on the console or by using the SDK. The following CLI command will upgrade an eligible cluster immediately:

For Linux, OS X, or Unix:

aws neptune modify-db-cluster \ --db-cluster-identifier (your-neptune-cluster) \ --engine-version \ --apply-immediately

For Windows:

aws neptune modify-db-cluster ^ --db-cluster-identifier (your-neptune-cluster) ^ --engine-version ^ --apply-immediately

Updates are applied to all instances in a DB cluster simultaneously. An update requires a database restart on those instances, so you will experience downtime ranging from 20–30 seconds to several minutes, after which you can resume using the DB cluster.

For more information about upgrading your engine version, see Neptune engine updates. If you have any questions or concerns, the Amazon Support team is available on the community forums and through Amazon Premium Support.