Update the table with the scalability options

Author: renetapopova

modules/ROOT/pages/scalability/scaling-with-neo4j.adoc

@@ -37,70 +37,72 @@ The main advantage is obtained by combining Neo4j clustering and composite datab
 label:preview[Preview feature] xref:scalability/sharded-property-databases/overview.adoc[Property sharding] (part of Infinigraph) allows you to decouple the properties attached to nodes and relationships and store them in separate graphs.
 This architecture enables the independent scaling of property data, allowing for the handling of high volumes, heavy queries, and high read concurrency.
 
-The following table summarizes the similarities and differences between analytics clustering, composite databases and sharded property databases:
+The following table summarizes the similarities and differences between analytics clustering, composite databases, and sharded property databases:
 
-.Similarities and differences between analytics clustering, composite databases and sharded property databases
+.Similarities and differences between analytics cluster, composite databases, and sharded property databases
 [cols="2,4a,4a,4a",frame="topbot",options="header"]
 |===
 |
 | Analytics cluster
 | Composite database
 | Sharded property database
 
-
-| Typical use cases
-|
-| *Federated data* +
+| *Typical use cases*
+| High Availability +
+GDS dedicated server
+| Federated data +
 Time-based sharding +
-*Application-based access*
-| *Graphs with a large volume of properties* +
+Application-based access
+| Graphs with a large volume of properties +
 Ideal for vector and full-text search
 
-| Scalability
-|
-| *Data volume: unlimited* +
-Read concurrency: horizontal scale on multiple instances +
-*Write concurrency: horizontal scale depending on the graph model*
-| *Data volume: up to 100TB* +
-Read concurrency: horizontal scale on multiple instances +
-*Write concurrency: single instance*
-
-| Transactions
-|
+| *Scalability*
+| *Data volume:* limited to single server size +
+*Read concurrency*: horizontal scale on multiple instances
+| *Data volume:* unlimited +
+*Read concurrency*: horizontal scale on multiple instances +
+*Write concurrency*: horizontal scale depending on the graph model
+| *Data volume:* up to 100TB +
+*Read concurrency*: horizontal scale on multiple instances +
+*Write concurrency*: single instance
+
+| *Transactions*
+| Causal consistency +
+Standard transaction management
 | Parallel read transactions +
 Single-shard write transactions +
 `CALL {} IN TRANSACTION` for multiple, isolated read/write transactions with manual error handling
 | Parallel read & write transactions on all shards +
 Standard transaction management
 
-| Data load
-|
+| *Data load*
+| Initial and incremental data import via neo4j-admin and Aura importer
 | Manually orchestrated import +
 Ad-hoc, project-based, sharded import
 | Initial and incremental data import via neo4j-admin and Aura importer
 
-| Cypher queries
-|
+| *Cypher queries*
+| Single database queries.
 | Parallel execution on shards. +
-Single database queries must be modified according to the *sharding rules*. +
+Single database queries must be modified according to the sharding rules. +
 Automated shard pruning using sharding functions.
 | Parallel execution on shards. +
-Single database *queries run as is*. +
+Single database queries run as is. +
 Automated shard pruning based on node selection.
 
-| User tools
-|
+| *User tools*
+| All tools supported.
 | Work with Browser and Cypher Shell. +
 Tools used on individual shards and Bloom are not supported on composite databases.
 | All tools supported.
 
-| Admin tools
-|
+| *Admin tools*
+| All tools supported.
 | Tools used on individual shards are not supported on composite databases.
 | All tools supported.
 
-| Libraries
-|
+| *Libraries*
+| All libraries supported.
 | Supported on individual shards.
 | All libraries supported.
 |===