DO NOT USE: Pebble is an incomplete work-in-progress.
Pebble 
Pebble is a LevelDB/RocksDB inspired key-value store focused on performance and internal usage by CockroachDB. Pebble inherits the RocksDB file formats and a few extensions such as range deletion tombstones, table-level bloom filters, and updates to the MANIFEST format.
Pebble intentionally does not aspire to include every feature in RocksDB and is specifically targetting the use case and feature set needed by CockroachDB:
- Block-based tables
- Indexed batches
- Iterator options (lower/upper bound, table filter)
- Level-based compaction
- Manual compaction
- Merge operator
- Prefix bloom filters
- Range deletion tombstones
- Prefix iteration
- Reverse iteration
- Snapshots
- SSTable ingestion
- Table-level bloom filters
RocksDB has a large number of features that are not implemented in Pebble:
- Backups and checkpoints
- Column families
- Delete files in range
- FIFO compaction style
- Forward iterator / tailing iterator
- Hash table format
- Memtable bloom filter
- Persistent cache
- Pin iterator key / value
- Plain table format
- Single delete
- SSTable ingest-behind
- Sub-compactions
- Transactions
- Universal compaction style
Pebble may silently corrupt data or behave incorrectly if used with a RocksDB database that uses a feature Pebble doesn't support. Caveat emptor!
Advantages
Pebble offers several improvements over RocksDB:
- Faster reverse iteration via backwards links in the memtable's skiplist.
- Faster commit pipeline that achieves better concurrency.
- Seamless merged iteration of indexed batches. The mutations in the batch conceptually occupy another memtable level.
- Smaller, more approachable code base.
- Pacing of flushes vs compactions: Pebble smooths latency spikes caused by flushes and compactions by only flushing/compacting as fast as necessary to keep up with user writes.
Pedigree
Pebble is based on the incomplete Go version of LevelDB:
https://github.com/golang/leveldb
The Go version of LevelDB is based on the C++ original:
https://github.com/google/leveldb
Optimizations and inspiration were drawn from RocksDB: