A Solr collection's schema — fields, types, analyzers, copy-field rules — decides how every search behaves. DbSchema connects over the SolrJ JDBC driver and diagrams that field structure, with SQL querying and browsable documentation on top.
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How a field is tokenized, which copy-field rules feed it, whether it is stored or only indexed — Solr keeps all of it in configuration files that grow denser with every tuning pass. Inherit a collection, and the schema is an archaeology project.
DbSchema introspects the collection and shows the field structure as a diagram — the search engine's contract, finally at a glance.
Field structure, SQL access, and documentation for search teams.
Connect to a core or collection and DbSchema renders every defined field with its type — the structure behind the search, without opening a config file.
Solr's Streaming Expressions translate a SQL subset into distributed queries; DbSchema's editor adds collection and field completion, plus COUNT, SUM, and AVG where the engine supports them.
Export the field schema as offline documentation for the application developers integrating search — which fields exist, their types, and what they mean.
The DbSchema model is a file that lives happily next to your Solr configset in Git. A new field or a changed type becomes a visible diff teammates approve in review — the same ritual your code already goes through, now covering the search schema.
Add the SolrJ JDBC driver
(org.apache.solr.client.solrj.io.sql.DriverImpl) in DbSchema's driver manager and
use a URL like jdbc:solr://localhost:8983?collection=mycollection — 8983
is Solr's default HTTP port, and the parameter names the collection to query. In SolrCloud, any
node of the cluster works as the target, with ZooKeeper handling routing; secured clusters take
username and password parameters or a Kerberos setup, depending on your
configuration.
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Teams working with Apache Solr often use these engines too. Explore dedicated guides and JDBC setup for each.