Hazelcast allows you to load and store the distributed map entries from/to a persistent data store such as a relational database. To do this, you can use Hazelcast's MapStore and MapLoader interfaces.

When you provide a MapLoader implementation and request an entry (IMap.get()) that does not exist in memory, MapLoader's load or loadAll methods will load that entry from the data store. This loaded entry is placed into the map and will stay there until it is removed or evicted.

When a MapStore implementation is provided, an entry is also put into a user defined data store.

image NOTE: Data store needs to be a centralized system that is accessible from all Hazelcast members. Persistence to a local file system is not supported.

image NOTE: Also note that the MapStore interface extends the MapLoader interface as you can see in the interface code.

Following is a MapStore example.

public class PersonMapStore implements MapStore<Long, Person> {
    private final Connection con;

    public PersonMapStore() {
        try {
            con = DriverManager.getConnection("jdbc:hsqldb:mydatabase", "SA", "");
                    "create table if not exists person (id bigint, name varchar(45))");
        } catch (SQLException e) {
            throw new RuntimeException(e);

    public synchronized void delete(Long key) {
        System.out.println("Delete:" + key);
        try {
                    format("delete from person where id = %s", key));
        } catch (SQLException e) {
            throw new RuntimeException(e);

    public synchronized void store(Long key, Person value) {
        try {
                    format("insert into person values(%s,'%s')", key, value.name));
        } catch (SQLException e) {
            throw new RuntimeException(e);

    public synchronized void storeAll(Map<Long, Person> map) {
        for (Map.Entry<Long, Person> entry : map.entrySet())
            store(entry.getKey(), entry.getValue());

    public synchronized void deleteAll(Collection<Long> keys) {
        for (Long key : keys) delete(key);

    public synchronized Person load(Long key) {
        try {
            ResultSet resultSet = con.createStatement().executeQuery(
                    format("select name from person where id =%s", key));
            try {
                if (!resultSet.next()) return null;
                String name = resultSet.getString(1);
                return new Person(name);
            } finally {
        } catch (SQLException e) {
            throw new RuntimeException(e);

    public synchronized Map<Long, Person> loadAll(Collection<Long> keys) {
        Map<Long, Person> result = new HashMap<Long, Person>();
        for (Long key : keys) result.put(key, load(key));
        return result;

    public Iterable<Long> loadAllKeys() {
        return null;

image NOTE: During the initial loading process, MapStore uses a thread different from the partition threads that are used by the ExecutorService. After the initialization is completed, the map.get method looks up any nonexistent value from the database in a partition thread, or the map.put method looks up the database to return the previously associated value for a key also in a partition thread.


For more MapStore/MapLoader code samples, please see here.

Hazelcast supports read-through, write-through, and write-behind persistence modes, which are explained in the subsections below.

Using Read-Through Persistence

If an entry does not exist in memory when an application asks for it, Hazelcast asks the loader implementation to load that entry from the data store. If the entry exists there, the loader implementation gets it, hands it to Hazelcast, and Hazelcast puts it into memory. This is read-through persistence mode.

Setting Write-Through Persistence

MapStore can be configured to be write-through by setting the write-delay-seconds property to 0. This means the entries will be put to the data store synchronously.

In this mode, when the map.put(key,value) call returns:

  • MapStore.store(key,value) is successfully called so the entry is persisted.
  • In-Memory entry is updated.
  • In-Memory backup copies are successfully created on other cluster members (if backup-count is greater than 0).

If MapStore throws an exception then the exception is propagated to the original put or remove call in the form of RuntimeException.

image NOTE: There is a key difference in the behaviors of map.remove(key) and map.delete(key), i.e., the latter results in MapStore.delete(key) to be invoked whereas the former only removes the entry from IMap.

Setting Write-Behind Persistence

You can configure MapStore as write-behind by setting the write-delay-seconds property to a value bigger than 0. This means the modified entries will be put to the data store asynchronously after a configured delay.

image NOTE: In write-behind mode, Hazelcast coalesces updates on a specific key by default, which means it applies only the last update on that key. However, you can set MapStoreConfig#setWriteCoalescing to FALSE and you can store all updates performed on a key to the data store.

image NOTE: When you set MapStoreConfig#setWriteCoalescing to FALSE, after you reached per-node maximum write-behind-queue capacity, subsequent put operations will fail with ReachedMaxSizeException. This exception will be thrown to prevent uncontrolled grow of write-behind queues. You can set per-node maximum capacity using the system property hazelcast.map.write.behind.queue.capacity. Please refer to the System Properties section for information on this property and how to set the system properties.

In write-behind mode, when the map.put(key,value) call returns:

  • In-Memory entry is updated.
  • In-Memory backup copies are successfully created on other cluster members (if backup-count is greater than 0).
  • The entry is marked as dirty so that after write-delay-seconds, it can be persisted with MapStore.store(key,value) call.
  • For fault tolerance, dirty entries are stored in a queue on the primary member and also on a back-up member.

The same behavior goes for the map.remove(key), the only difference is that MapStore.delete(key) is called when the entry will be deleted.

If MapStore throws an exception, then Hazelcast tries to store the entry again. If the entry still cannot be stored, a log message is printed and the entry is re-queued.

For batch write operations, which are only allowed in write-behind mode, Hazelcast will call MapStore.storeAll(map) and MapStore.deleteAll(collection) to do all writes in a single call.

image NOTE: If a map entry is marked as dirty, meaning that it is waiting to be persisted to the MapStore in a write-behind scenario, the eviction process forces the entry to be stored. This way you have control over the number of entries waiting to be stored, and thus you can prevent a possible OutOfMemory exception.

image NOTE: MapStore or MapLoader implementations should not use Hazelcast Map/Queue/MultiMap/List/Set operations. Your implementation should only work with your data store. Otherwise, you may get into deadlock situations.

Here is a sample configuration:

  <map name="default">
    <map-store enabled="true" initial-mode="LAZY">

The following are the descriptions of MapStore configuration elements and attributes:

  • class-name: Name of the class implementing MapLoader and/or MapStore.
  • write-delay-seconds: Number of seconds to delay to call the MapStore.store(key, value). If the value is zero then it is write-through so MapStore.store(key, value) will be called as soon as the entry is updated. Otherwise it is write-behind so updates will be stored after write-delay-seconds value by calling Hazelcast.storeAll(map). Default value is 0.
  • write-batch-size: Used to create batch chunks when writing map store. In default mode, all map entries will be tried to be written in one go. To create batch chunks, the minimum meaningful value for write-batch-size is 2. For values smaller than 2, it works as in default mode.
  • write-coalescing: In write-behind mode, Hazelcast coalesces updates on a specific key by default; it applies only the last update on it. You can set this element to false to store all updates performed on a key to the data store.
  • enabled: True to enable this map-store, false to disable. Default value is true.
  • initial-mode: Sets the initial load mode. LAZY is the default load mode, where load is asynchronous. EAGER means load is blocked till all partitions are loaded.

Storing Entries to Multiple Maps

A configuration can be applied to more than one map using wildcards (see Using Wildcards), meaning that the configuration is shared among the maps. But MapStore does not know which entries to store when there is one configuration applied to multiple maps.

To store entries when there is one configuration applied to multiple maps, use Hazelcast's MapStoreFactory interface. Using the MapStoreFactory interface, MapStores for each map can be created when a wildcard configuration is used. Example code is shown below.

Config config = new Config();
MapConfig mapConfig = config.getMapConfig( "*" );
MapStoreConfig mapStoreConfig = mapConfig.getMapStoreConfig();
mapStoreConfig.setFactoryImplementation( new MapStoreFactory<Object, Object>() {
  public MapLoader<Object, Object> newMapStore( String mapName, Properties properties ) {
    return null;

To initialize the MapLoader implementation with the given map name, configuration properties, and the Hazelcast instance, implement the MapLoaderLifecycleSupport interface. This interface has the methods init() and destroy() as shown below.

public interface MapLoaderLifecycleSupport {

  void init( HazelcastInstance hazelcastInstance, Properties properties, String mapName );

  void destroy();

The method init() initializes the MapLoader implementation. Hazelcast calls this method when the map is first used on the Hazelcast instance. The MapLoader implementation can initialize the required resources for implementing MapLoader such as reading a configuration file or creating a database connection.

Hazelcast calls the method destroy() before shutting down. You can override this method to cleanup the resources held by this MapLoader implementation, such as closing the database connections.

Initializing Map on Startup

To pre-populate the in-memory map when the map is first touched/used, use the MapLoader.loadAllKeys API.

If MapLoader.loadAllKeys returns NULL, then nothing will be loaded. Your MapLoader.loadAllKeys implementation can return all or some of the keys. For example, you may select and return only the hot keys. MapLoader.loadAllKeys is the fastest way of pre-populating the map since Hazelcast will optimize the loading process by having each cluster member load its owned portion of the entries.

The InitialLoadMode configuration parameter in the class MapStoreConfig has two values: LAZY and EAGER. If InitialLoadMode is set to LAZY, data is not loaded during the map creation. If it is set to EAGER, all the data is loaded while the map is created, and everything becomes ready to use. Also, if you add indices to your map with the MapIndexConfig class or the addIndex method, then InitialLoadMode is overridden and MapStoreConfig behaves as if EAGER mode is on.

Here is the MapLoader initialization flow:

  1. When getMap() is first called from any member, initialization will start depending on the value of InitialLoadMode. If it is set to EAGER, initialization starts on all partitions as soon as the map is touched, i.e., all partitions will be loaded when getMap is called. If it is set to LAZY, data will be loaded partition by partition, i.e., each partition will be loaded with its first touch.
  2. Hazelcast will call MapLoader.loadAllKeys() to get all your keys on one of the members.
  3. That member will distribute keys to all other members in batches.
  4. Each member will load values of all its owned keys by calling MapLoader.loadAll(keys).
  5. Each member puts its owned entries into the map by calling IMap.putTransient(key,value).

image NOTE: If the load mode is LAZY and the clear() method is called (which triggers MapStore.deleteAll()), Hazelcast will remove ONLY the loaded entries from your map and datastore. Since all the data is not loaded in this case (LAZY mode), please note that there may still be entries in your datastore.

image NOTE: If you do not want the MapStore start to load as soon as the first cluster member starts, you can use the system property hazelcast.initial.min.cluster.size. For example, if you set its value as 3, loading process will be blocked until all three members are completely up.

image NOTE: The return type of loadAllKeys() is changed from Set to Iterable with the release of Hazelcast 3.5. MapLoader implementations from previous releases are also supported and do not need to be adapted.

Loading Keys Incrementally

If the number of keys to load is large, it is more efficient to load them incrementally rather than loading them all at once. To support incremental loading, the MapLoader.loadAllKeys() method returns an Iterable which can be lazily populated with the results of a database query.

Hazelcast iterates over the Iterable and, while doing so, sends out the keys to their respective owner members. The Iterator obtained from MapLoader.loadAllKeys() may also implement the Closeable interface, in which case Iterator is closed once the iteration is over. This is intended for releasing resources such as closing a JDBC result set.

Forcing All Keys To Be Loaded

The method loadAll loads some or all keys into a data store in order to optimize the multiple load operations. The method has two signatures; the same method can take two different parameter lists. One signature loads the given keys and the other loads all keys. Please see the example code below.

public class LoadAll {

    public static void main(String[] args) {
        final int numberOfEntriesToAdd = 1000;
        final String mapName = LoadAll.class.getCanonicalName();
        final Config config = createNewConfig(mapName);
        final HazelcastInstance node = Hazelcast.newHazelcastInstance(config);
        final IMap<Integer, Integer> map = node.getMap(mapName);
        populateMap(map, numberOfEntriesToAdd);
        System.out.printf("# Map store has %d elements\n", numberOfEntriesToAdd);
        System.out.printf("# After evictAll map size\t: %d\n", map.size());
        System.out.printf("# After loadAll map size\t: %d\n", map.size());

Post-Processing Objects in Map Store

In some scenarios, you may need to modify the object after storing it into the map store. For example, you can get an ID or version auto-generated by your database and then need to modify your object stored in the distributed map, but not to break the synchronization between the database and the data grid.

To post-process an object in the map store, implement the PostProcessingMapStore interface to put the modified object into the distributed map. This will trigger an extra step of Serialization, so use it only when needed. (This is only valid when using the write-through map store configuration.)

Here is an example of post processing map store:

class ProcessingStore implements MapStore<Integer, Employee>, PostProcessingMapStore {
  public void store( Integer key, Employee employee ) {
    EmployeeId id = saveEmployee();
    employee.setId( id.getId() );

image NOTE: Please note that if you are using a post processing map store in combination with entry processors, post-processed values will not be carried to backups.

Accessing a Database Using Properties

You can prepare your own MapLoader to access a database such as Cassandra and MongDB. For this, you can first declaratively specify the database properties in your hazelcast.xml configuration file and then implement the MapLoaderLifecycleSupport interface to pass those properties.

You can define the database properties, such as its URL and name, using the properties configuration element. The following is a configuration example for MongoDB:

    <map name="supplements">
        <map-store enabled="true" initial-mode="LAZY">
                <property name="mongo.url">mongodb://localhost:27017</property>
                <property name="mongo.db">mydb</property>
                <property name="mongo.collection">supplements</property>

After you specified the database properties in your configuration, you need to implement the MapLoaderLifecycleSupport interface and give those properties in the init() method, as shown below:

public class YourMapStoreImplementation implements MapStore<String, Supplement>, MapLoaderLifecycleSupport {

    private MongoClient mongoClient;
    private MongoCollection collection;

    public YourMapStoreImplementation() {

    public void init(HazelcastInstance hazelcastInstance, Properties properties, String mapName) {
        String mongoUrl = (String) properties.get("mongo.url");
        String dbName = (String) properties.get("mongo.db");
        String collectionName = (String) properties.get("mongo.collection");
        this.mongoClient = new MongoClient(new MongoClientURI(mongoUrl));
        this.collection = mongoClient.getDatabase(dbName).getCollection(collectionName);

You can refer to the full example here.