Chronicle Map is an in-memory, key-value store, designed for low-latency, and/or multi-process applications, such as trading and financial market applications.
-
Ultra low latency: Chronicle Map targets median latency of both read and write queries of less than 1 microsecond in certain tests.
-
High concurrency: Write queries scale well up to the number of hardware execution threads in the server. Read queries never block each other.
-
Persistence to disk - (Optional)
-
Replication - (Optional, commercial functionality) - replication from one to N other servers across LAN/WAN
-
Multiple processes can access a Chronicle Map concurrently. At the same time, the data store is in-process for each of the accessing processes. Out-of-process approach to IPC is simply incompatible with Chronicle Map’s median latency target of < 1 μs.
-
Replication
Note
|
See Chronicle Map Replication for more information. |
Chronicle Map has two meanings:
-
implementation of this data store for the JVM (source). Currently, this is the only implementation.
ChronicleMap
is a ConcurrentMap
implementation which stores the
entries off-heap, serializing/deserializing key and value objects to/from off-heap memory
transparently. Chronicle Map supports:
-
Key and value objects caching/reusing for making zero allocations (garbage) on queries.
-
Flyweight values for eliminating serialization/deserialization cost and allowing direct read/write access to off-heap memory.
-
Replacing slower key-value stores, like
Redis
andMemcached
, when used within a single server. -
Replacing similar JVM-centric solutions, like
Coherence
andHazelcast
, for speed and/or certain Chronicle Map features which those solutions lack. -
Moving parts of the application-state out of the Java heap for either:
-
Reducing the heap size, for reducing garbage collection pressure, or fitting 32 GB, for using
CompressedOops
. -
Inter-process communication.
-
Persistence.
-
Replication across servers.
-
-
Drop-in
ConcurrentHashMap
replacement; Chronicle Map performs better in some cases.
-
Atomicity - single-key queries are atomic if Chronicle Map is properly configured, multi-key queries are not atomic.
-
Consistency - doesn’t make sense for key-value stores
-
Isolation - yes; for both single- and multi-key queries.
-
Durability - no; Chronicle Map can be persisted to disk, but with no guarantee as to how frequently this happens. This is under the control of the OS. All data is guaranteed to be written to disk when the Map is closed.
-
Clustering and replication for Chronicle Map is provided by Chronicle Queue Enterprise.
Simply put, a Chronicle Map data store is a big chunk of shared memory (optionally mapped to disk).
It is split into independent segments; each segment has:
-
an independent memory allocation for storing the entries
-
a hash table for search
-
a lock in shared memory (implemented via CAS loops) for managing concurrent access.
See Chronicle Map data store design overview for more information.
-
A document store. There are no secondary indexes.
-
A multimap. Using a Chronicle Map collection as a multimap is technically possible, but often leads to problems. See StackOverflow answer for details. Developing a proper multimap, using Chronicle Map’s design principles is possible.
Please contact us at sales@chronicle.software if you would consider sponsoring such development.
-
range queries.
-
iteration over the entries in alphabetical order.
-
sorting of keys.
-
LRU entry eviction.
Feature | Availability |
---|---|
In-memory off-heap Map |
Open source |
Persistence to disk |
Open source |
Remote calls |
Commercially available |
Replication |
Commercially available |
Synchronous replication |
Commercially available |
Partially-redundant replication |
On demand |
Entry expiration timeouts |
On demand |
Note
|
For access to commercially available features please contact sales@chronicle.software. |