From 0cab1c60328cccb891b1098b87c8e873394426a9 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jens=20Pryce-=C3=85klundh?=
 <112686610+JPryce-Aklundh@users.noreply.github.com>
Date: Tue, 23 Jan 2024 14:06:03 +0100
Subject: [PATCH] remove release version on concepts page

---
 modules/ROOT/pages/planning-and-tuning/runtimes/concepts.adoc | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/ROOT/pages/planning-and-tuning/runtimes/concepts.adoc b/modules/ROOT/pages/planning-and-tuning/runtimes/concepts.adoc
index fabec252a..c40aa1dc5 100644
--- a/modules/ROOT/pages/planning-and-tuning/runtimes/concepts.adoc
+++ b/modules/ROOT/pages/planning-and-tuning/runtimes/concepts.adoc
@@ -311,7 +311,7 @@ Batch size 128
 A key difference between the physical plans produced by the parallel runtime compared to those generated by pipelined runtime is that, in general, more pipelines are produced when using the parallel runtime (in this case, seven instead of the four produced by the same query being run on pipelined runtime).
 This is because, when executing a query in the parallel runtime, it is more efficient to have more tasks that can be run in parallel, whereas when running a single-threaded execution in the pipelined runtime it is more efficient to fuse several pipelines together.
 
-Another important difference is that, since the release of Neo4j 5.17, the parallel runtime uses partitioned operators (xref:planning-and-tuning/operators/operators-detail.adoc#query-plan-partitioned-node-by-label-scan[`PartitionedNodeByLabelScan`] in this case).
+Another important difference is that the parallel runtime uses partitioned operators (xref:planning-and-tuning/operators/operators-detail.adoc#query-plan-partitioned-node-by-label-scan[`PartitionedNodeByLabelScan`] in this case).
 These operators first segment the retrieved data and then operate on each segment in parallel.
 
 The parallel runtime shares the same architecture as the pipelined runtime, meaning that it will transform the logical plan into the same type of execution graph as described above.