Terrastore: All content tagged as Terrastore in NoSQL databases and polyglot persistence
Such list would be even more useful with the following classification:
Note: A special mention in this category for OrientDB and Terrastore which even if they might not be largely adopted they are still active projects probably counting a couple of production deployments.
Original title and link: 11 Document-Oriented Databases Which Are 8: CouchDB, Jackrabbit, MongoDB, RavenDB ( ©myNoSQL)
After a short break, Terrastore has published a new version, 0.8.0, which brings quite a few interesting features, plus some performance, scalability, and stability enhancements:
- map/reduce processing
- active event listeners
- adaptive ensemble scheduling
- document and communication compression
Sergio Bossa, Terrastore lead developer, has shared more about this release ☞ here:
Terrastore map/reduce implementation targets all documents, or just a subset of documents specified by range, belonging to a single bucket, and is based on three phases: mapper, combiner and reducer. The mapper phase is initiated by the node which received the map/reduce request, the originator node: it locates the target documents and the nodes that hold them, then sends the map function to those node so that it can be applied in parallel on each node; the map function will take each target document as input argument, and return, for each document, a map of
pairs as output. Then, each remote node runs the combiner phase, aggregating its local map results and returning a partial map of pairs. Finally, the originator node runs the reducer phase, aggregating all partial results.
You can download the new Terrastore from ☞ here.
From Sergio Bossa’s (@sbtourist) slides embedded below:
Terrastore is best suited for:
- data hot spots
- computational data
- complex, rich or variable data
- throw-away data
Quite generic, so I’d love to hear from those that are planning to use Terrastore in their projects.
Not sure how long is supposed to stay online, so check Mats Henricson’s slides on CRUD with Terrastore while they are ☞ here:
- Built on top of Terracotta!
- HTTP and Java API
- Supports single-cluster and multi-cluster deployments
- Elastic: You can add and remove nodes dynamically
- Scalable: Automatic and transparent re-balancing
- Easy to install and configure
- Custom data partitioning
- Event processing
- Range queries
- Server-side update functions
- Per-document consistency
Last week Terrastore has seen a new release, 0.6.0, featuring a few interesting improvements:
- Reduced overall memory footprint, allowing for higher performance.
- Improved range queries performance and scalability.
- Reliable event publishing by integrating with the ActiveMQ message broker.
- Several new predicate conditions and update functions, improving Terrastore built-in data processing capabilities.
You can find out more about Terrastore data processing capabilities in our interview with Terrastore lead developer, Sergio Bossa.