Hello, I've been considering JackRabbit as a potential replacement for a traditional RDBMS content repository we've been using. Currently, the metadata is very "static" from document to document. However, we want to start bringing in arbitrary types of documents. Each document will specify its own metadata, and may map "core" metadata back to a set of common fields. It really seems like a natural fit for JCR.
I don't really need search (search services will be provided by a separately synchronized and already existing index), but I do need content scalability. We have about 500GB worth of binary data and 1GB of associated text metadata right now (about 200k records). Ideally, the repository would contain the binary data as the primary node, rather than merely referencing it. However, this already large data set will probably grow up to 2-3TB in the next year and potentially way beyond that, with millions of records.
From browsing the archives, it seems like this would be well above and
beyond the typical repository size. Has anybody used Jackrabbit with this volume of data? It is pretty difficult to set up a test, so I'm left to rely on similar user experience. Would clustering, workspace partitioning, etc handle the volume we'd be expected to produce? Thanks for the help, Cris
