Legal software specialist Aderant offers Handshake, the company's Sharepoint compatible knowledge management platform specifically for law firms featuring access via intranet and extranet portals and an enterprise search tool for locating documentation and expertise, and general KM analytics.
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Apache Solr
Score 6.6 out of 10
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Apache Solr is an open-source enterprise search server.
The user of Handshake takes a certain amount of user computer literacy and the user needs to be resourceful. When building our site, I needed to google quite a bit. On the contrary, if budget allows, Handshake developers will do it all for you.
Solr spins up nicely and works effectively for small enterprise environments providing helpful mechanisms for fuzzy searches and facetted searching. For larger enterprises with complex business solutions you'll find the need to hire an expert Solr engineer to optimize the powerful platform to your needs. Internationalization is tricky with Solr and many hosting solutions may limit you to a latin character set.
The main reason we got Handshake was to display visual gadgets for our accounting systems. We always provided spreadsheet type reports, but pictures and more engaging. Attorney gets a dashboard in real time of where they stand financially.
Additional use as FAQ's in different departments in the firm, that is, accounting, IT, and office services.
Easy to get started with Apache Solr. Whether it is tackling a setup issue or trying to learn some of the more advanced features, there are plenty of resources to help you out and get you going.
Performance. Apache Solr allows for a lot of custom tuning (if needed) and provides great out of the box performance for searching on large data sets.
Maintenance. After setting up Solr in a production environment there are plenty of tools provided to help you maintain and update your application. Apache Solr comes with great fault tolerance built in and has proven to be very reliable.
These examples are due to the way we use Apache Solr. I think we have had the same problems with other NoSQL databases (but perhaps not the same solution). High data volumes of data and a lot of users were the causes.
We have lot of classifications and lot of data for each classification. This gave us several problems:
First: We couldn't keep all our data in Solr. Then we have all data in our MySQL DB and searching data in Solr. So we need to be sure to update and match the 2 databases in the same time.
Second: We needed several load balanced Solr databases.
Third: We needed to update all the databases and keep old data status.
If I don't speak about problems due to our lack of experience, the main Solr problem came from frequency of updates vs validation of several database. We encountered several locks due to this (our ops team didn't want to use real clustering, so all DB weren't updated). Problem messages were not always clear and we several days to understand the problems.
