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commit 019b860464e74bc6ece840ab709a474573bbdb7f
Author: Stephen Mallette <stepm...@amazon.com>
AuthorDate: Thu Jul 3 09:28:16 2025 -0400
Minor updates to TinkerGraph docs CTR
---
docs/src/reference/implementations-tinkergraph.asciidoc | 14 +++++++++-----
1 file changed, 9 insertions(+), 5 deletions(-)
diff --git a/docs/src/reference/implementations-tinkergraph.asciidoc
b/docs/src/reference/implementations-tinkergraph.asciidoc
index f0ba65f1ce..592adff319 100644
--- a/docs/src/reference/implementations-tinkergraph.asciidoc
+++ b/docs/src/reference/implementations-tinkergraph.asciidoc
@@ -27,17 +27,21 @@ limitations under the License.
----
image:tinkerpop-character.png[width=100,float=left] TinkerGraph is a single
machine, in-memory (with optional
-persistence), non-transactional graph engine that provides both OLTP and OLAP
functionality. It is deployed with
-TinkerPop and serves as the reference implementation for other providers to
study in order to understand the
-semantics of the various methods of the TinkerPop API. Its status as a
reference implementation does not however imply
-that it is not suitable for production. TinkerGraph has many practical use
cases in production applications and their
-development. Some examples of TinkerGraph use cases include:
+persistence), graph engine that provides both OLTP and OLAP functionality. It
is non-transactional by default but does
+have a lightweight transactional form that can be instantiated offering simple
`ThreadLocal` transactions supporting
+`read committed` transaction isolation. TinkerGraph is deployed with TinkerPop
and serves as the reference
+implementation for other providers to study in order to understand the
semantics of the various methods of the
+TinkerPop API. Its status as a reference implementation does not however imply
that it is not suitable for production.
+TinkerGraph has many practical use cases in production applications and their
development. Some examples of TinkerGraph
+use cases include:
* Ad-hoc analysis of large immutable graphs that fit in memory.
* Extract subgraphs, from larger graphs that don't fit in memory, into
TinkerGraph for further analysis or other
purposes.
* Use TinkerGraph as a sandbox to develop and debug complex traversals by
simulating data from a larger graph inside
a TinkerGraph.
+* Configure it to match the semantics of a production graph database for unit
testing purpose to simplify development
+setup and automated builds.
Constructing a simple graph using TinkerGraph in Java is presented below:
