HyperSQL has multiple deployment and persistence options which influence its
- The table type, MEMORY, CACHED or TEXT, indicates how the table row data
is stored and accessed by the database engine.
- In-process or server mode indicates how all the database engine data is
accessed by the user's application.
- The transaction model indicates how and when different sessions
(connections) wait for one another.
- Use of BLOBS and CLOBS
The performance characteristics of different table types are:
- MEMORY tables provide the highest performance. All data is in memory and
each field of each row is a memory object that can be read by the database
engine without any conversion. When data is updated, only a log record is
written to disk, usually with a fixed overhead per row.
- CACHED tables have a lower performance compared to MEMORY tables. Data
for this type of table comes from a row cache (hence the name) which at any
time holds a subset of all the rows in all CACHED tables. Reduction in
performance is due to three reasons.
- First, because the size of the row cache is usually smaller than the
total row count of all the CACHED tables, rows are frequently purged
from the cache and other rows are read from the disk and converted into
- Second, even if the row cache is large enough to hold all the rows
that are accessed by the user's application in a period of time, the
extra layer of access adds a small overhead.
- Third, because data updates are both logged and written to the data
file, there is a larger overhead for data updates.
- TEXT tables have similarities to both CACHED tables and MEMORY tables.
The indexes are held in memory, while the data is held on disk and cached
like CACHED tables. Because the data is stored in text form as comma
separated values (CSV) or similar formats, reading and writing the data
takes longer than the same operation in binary format. On the other hand,
because the indexes are in memory and no separate logging is performed,
write operations may be faster than CACHED tables.
In-process and Server
The performance characteristics of in-process versus server mode are:
- In-process access takes place in the same memory space as the user's
application. There is no data conversion or network transfer overhead
- Server mode usually has a different memory space than the user's
application. The data is converted into a byte stream, transferred over the
network, and then converted back into objects. This introduces latency plus
the extra processing needed for conversion.
- HyperSQL supports SQL and Java stored procedures, which allow a whole
transaction to be encapsulated in a single SQL statement. This speeds up
access in the server mode as a transaction can be completed in a single
network round trip, instead of execution of several statements. A single
call to a stored procedure can even return multiple result sets and return
values to the user's application.
HyperSQL supports MVCC and two phased locking transaction models. The
performance characteristics of the transaction model are:
- HyperSQL is fully multi threaded. If the vast majority of operations are
read operations, then performance is very high in all transaction models.
Multiple processes, each running in a different thread, can access the same
tables or rows at the same time and return the results independently to the
- If there is a significant amount of update operations, the 2PL lock model
performance can be reduced to a single thread. Because locks are kept both
for reads and writes, read operations on an updated table are delayed until
the writer commits, and similarly write operations are delayed until the
- The multiversion concurrency control (MVCC) model provides vastly greater
performance than the lock based model, as no read locks are used, while
write locks are kept only on the individual updated rows. Multiple threads
can read and update the database using multiple processor cores. This mode
is more performant than row level locking modes supported by some other
- With MVCC and multi processor cores, if there is spare processing power
and many concurrent sessions, the time overhead of network communications
will not affect the overall performance of the server mode deployments.
Each connection runs in a separate thread and uses the available processing
power for data conversion.
In summary, the fastest performance is typically achieved with the combination
of MEMORY tables
, in process access
and MVCC transaction model
. If reduced memory use
is required, some tables can be defined as CACHED tables, while keeping the
most frequently accessed tables as MEMORY tables. If server access
is required, then stored procedures
can be used to reduce the
network round trips.
Blobs and Clobs
HSQLDB is the only SQL open source database that supports a dedicated LOB
store. Blobs and clobs can be very large and benefit from a separate store that
avoids mixing their data with row data which is not too large. Internal
database tables are used for the LOB catalog. Therefore each access to a LOB
has the overhead of catalog lookup. This overhead is justified when the stored
LOBs are large. HSQLDB supports long VARCHAR and VARBINARY columns that can be
used instead of CLOB and BLOB especially when the average lob size is below 32
KB. These types do not have the LOB catalog overhead.
See the Performance Tests
page for some
benchmark test results.