Since revision 1.18 of the framework, a new SynDBDataset.pas unit has been introduced, able to interface any DB.pas based library to our SynDB classes, using TDataset to retrieve the results.
Due to the TDataset design, performance is somewhat degraded in respect to direct SynDB connection (e.g. results for SQLite3 or Oracle), but it also opens the potential database access.

Some dedicated providers have been published in the SynDBDataset sub-folder of the mORMot source code repository.
Up to now, FireDAC (formerly AnyDAC), UniDAC and BDE libraries are interfaced, and a direct connection to the NexusDB engine is available.

Since there are a lot of potential combinations here, feedback is welcome. Due to our Agile process, we will first stick to the providers we need and use. It is up to mORMot users to ask for additional features, and provide wrappers, if possible, or at least testing abilities. Of course, DBExpress would benefit to be integrated, even if Embarcadero just acquired AnyDAC and revamped/renamed it as FireDAC - to make it the new official platform.

Data access benchmark

On an recent notebook computer (Core i7 and SSD drive), depending on the back-end database interfaced, mORMot excels in speed:

  • You can persist up to 570,000 objects per second, or retrieve 870,000 objects per second (for our pure Delphi in-memory engine); 
  • When data is retrieved from server or client internal cache, you can read more than 900,000 objects per second, whatever the database back-end is; 
  • With a high-performance database like Oracle and our direct access classes, you can write 62,000 (via array binding) and read 92,000 objects per second, over a 100 MB network; 
  • When using alternate database access libraries (e.g. Zeos, or DB.pas based classes), speed is lower, but still enough for most work.

Those numbers include JSON serialization and object properties access via RTTI.
Difficult to find a faster ORM, I suspect.

The following tables try to sum up all available possibilities, and give some benchmark (average objects/second for writing or read).

In these tables:

  • 'SQLite3 (file full/off/exc)' indicates use of the internal SQLite3 engine, with or without Synchronous := smOff and/or DB.LockingMode := lmExclusive - see 60; 
  • 'SQLite3 (mem)' stands for the internal SQLite3 engine running in memory; 
  • 'SQLite3 (ext ...)' is about access to a SQLite3 engine as external database, either as file or memory; 
  • 'TObjectList' indicates a TSQLRestServerStaticInMemory instance - either static (with no SQL support) or virtual (i.e. SQL featured via SQLite3 virtual table mechanism) which may persist the data on disk as JSON or compressed binary; 
  • 'Oracle' shows the results of our direct OCI access layer (SynDBOracle.pas); 
  • 'Jet' stands for a MSAccess database engine, accessed via OleDB; 
  • 'NexusDB' is the free embedded edition, available from official site; 
  • 'ZEOS *' indicates that the database was accessed directly via the ZDBC layer; 
  • 'FireDAC *' stands for FireDAC library; 
  • 'UniDAC *' stands for UniDAC library; 
  • 'BDE *' when using a BDE connection; 
  • 'ODBC *' for a direct access to ODBC.

This list of database provider is to be extended in the future. Any feedback is welcome!

Numbers are expressed in rows/second (or objects/second).

Note that these tests are not about the relative speed of each database engine, but reflect the current status of the integration of several DB libraries within the mORMot database access.
Purpose here is not to say that one library is better or faster than another, but publish a snapshot of mORMot persistence layer abilities.

In this timing, we do not benchmark only the "pure" SQL/DB layer access (SynDB units), but the whole Client-Server ORM of our framework: process below includes read and write RTTI access of a TSQLRecord, JSON marshaling, CRUD/REST routing, virtual cross-database layer, SQL on-the-fly translation. We just bypass the communication layer, since TSQLRestClient and TSQLRestServer are run in-process, in the same thread - as a TSQLRestServerDB instance. So you have here some raw performance testimony of our framework's ORM and RESTful core.

You can compile the "15 - External DB performance" supplied sample code, and run the very same benchmark on your own configuration.

Insertion speed

Here we insert 5,000 rows of data, with diverse scenarios:

  • 'Direct' stands for a individual Client.Add() insertion; 
  • 'Batch' mode has already be described
  • 'Trans' indicates that all insertion is nested within a transaction - which makes a great difference, e.g. with a SQlite3 database.

Benchmark was run on a Core i7 notebook, with standard SSD, including anti-virus and background applications, over a 100 Mb corporate network, linked to a shared Oracle 11g database.
So it was a development environment, very similar to low-cost production site, not dedicated to give best performance.
During the process, CPU was noticeable used only for SQLite3 in-memory and TObjectList - most of the time, the bottleneck is not the CPU, but the storage or network.
As a result, rates and timing may vary depending on network and server load, but you get results similar to what could be expected on customer side, with an average hardware configuration.

  Direct Batch Trans Batch Trans
SQLite3 (file full) 503 399 96391 123064
SQLite3 (file off) 923 930 99534 130907
SQLite3 (file off exc) 31829 35798 101874 132752
SQLite3 (mem) 85803 109641 103976 135332
TObjectList (static) 321089 548365 312031 547105
TObjectList (virtual) 314366 513136 316676 571232
SQLite3 (ext full) 451 511 12092 137249
SQLite3 (ext off) 971 909 108133 144475
SQLite3 (ext off exc) 42805 51256 113155 150829
SQLite3 (ext mem) 97344 121400 113229 153256
ZEOS SQlite3 487 455 16826 19680
FireDAC SQlite3 25182 49795 41962 114241
UniDAC SQlite3 473 412 27370 37962
ZEOS Firebird 1835 2142 18734 22540
UniDAC Firebird 7065 7637 9157 10399
Jet 4197 4318 4789 4947
Oracle 511 59455 948 59762
ODBC Oracle 550 536 1024 1043
ZEOS Oracle 343 362 1086 1087
FireDAC Oracle 512 32328 980 34668
UniDAC Oracle 465 496 915 879
BDE Oracle 418 410 661 755
NexusDB 6278 6749 7901 8801

Due to its ACID implementation, SQLite3 process on file waits for the hard-disk to have finished flushing its data, therefore it is the reason why it is slower than other engines at individual row insertion (less than 10 objects per second with a mechanical hardrive instead of a SDD) outside the scope of a transaction.

So if you want to reach the best writing performance in your application with the default engine, you should better use transactions and regroup all writing into services or a BATCH process. Another possibility could be to execute DB.Synchronous := smOff and/or DB.LockingMode := lmExclusive at SQLite3 engine level before process: in case of power loss at wrong time it may corrupt the database file, but it will increase the rate by a factor of 50 (with hard drive), as stated by the "off" and "off exc" rows of the table. Note that by default, the FireDAC library set both options, so results above are to be compared with "SQLite3 off exc" rows.

For both our direct Oracle access SynDBOracle.pas library and FireDAC, Batch process benefit of the array binding feature a lot (known as Array DML in FireDAC/AnyDAC).

Reading speed

Now the same data is retrieved via the ORM layer:

  • 'By one' states that one object is read per call (ORM generates a SELECT * FROM table WHERE ID=? for Client.Retrieve() method); 
  • 'All *' is when all 5000 objects are read in a single call (i.e. running SELECT * FROM table from a FillPrepare() method call), either forced to use the virtual table layer, or with direct static call.

Here are some reading speed values, in objects/second:

  By one All Virtual All Direct
SQLite3 (file full) 26936 514456 531858
SQLite3 (file off) 27116 538735 428302
SQLite3 (file off exc) 122417 541125 541653
SQLite3 (mem) 119314 539781 545494
TObjectList (static) 303398 529661 799232
TObjectList (virtual) 308109 403323 871080
SQLite3 (ext full) 137525 264690 546806
SQLite3 (ext off) 134807 262123 531011
SQLite3 (ext off exc) 133936 261574 536941
SQLite3 (ext mem) 136915 258732 544069
ZEOS SQlite3 3232 83243 95934
FireDAC SQlite3 7639 80261 108117
UniDAC SQlite3 1586 73142 96989
ZEOS Firebird 3882 69974 85416
UniDAC Firebird 2177 71858 89856
Jet 2619 144801 222736
Oracle 593 74312 66131
ODBC Oracle 1134 33267 33049
ZEOS Oracle 863 44207 53868
FireDAC Oracle 896 33171 37912
UniDAC Oracle 500 21918 23688
BDE Oracle 689 3343 3426
NexusDB 1419 121294 195687

The SQLite3 layer gives amazing reading results, which makes it a perfect fit for most typical ORM use.
When running with DB.LockingMode := lmExclusive defined (i.e. "off exc" rows), reading speed is very high, and benefits from exclusive access to the database file.
External database access is only required when data is expected to be shared with other processes.

In the above table, it appears that all libraries based on DB.pas are slower than the others for reading speed.
In fact, TDataSet sounds to be a real bottleneck. Even FireDAC, which is known to be very optimized for speed, is limited by the TDataSet structure, especially during read speed.
Our direct classes, or even ZEOS/ZDBC performs better.

For both writing and reading, TObjectList / TSQLRestServerStaticInMemory engine gives impressive results, but has the weakness of being in-memory, so it is not ACID by design, and the data has to fit in memory.
Note that indexes are available for IDs and stored AS_UNIQUE properties.

Analysis and use case proposal

When declared as virtual table (via a VirtualTableRegister call), you have the full power of SQL (including JOINs) at hand, with incredibly fast CRUD operations: 100,000 requests per second for objects read and write, including serialization and Client-Server communication!

In the above list, the MS SQL Server is not integrated, but may be used instead of Oracle (minus the fact that BULK insert is not implemented yet for it, whereas array binding boosts Oracle writing BATCH process performance by 100 times). Any other OleDB or ODBC providers may also be used, with direct access. Or any DB.pas provider (e.g. DBExpress / BDE), but with the additional layer introduced by using a TDataSet instance.

Note that all those tests were performed locally and in-process, via a TSQLRestClientDB instance. For both insertion and reading, a Client-Server architecture (e.g. using HTTP/1.1 for mORMot clients) will give even better results for BATCH and retrieve all modes. During the tests, internal caching was disabled, so you may expect speed enhancements for real applications, when data is more read than written: for instance, when an object is retrieved from the cache, you achieve more than 700,000 read requests per second, whatever database is used.

Therefore, the typical use may be the following:

Database Created by Use
int. SQLite3 file default General safe data handling
int. SQLite3 mem :memory: Fast data handling with no persistence (e.g. for testing)
TObjectList static StaticDataCreate Best possible performance for small amount of data, without ACID nor SQL
TObjectList virtual VirtualTableRegister Best possible performance for small amount of data, if ACID is not required nor complex SQL
ext. SQLite3 file VirtualTableExternalRegister External back-end, e.g. for disk spanning
ext. SQLite3 mem VirtualTableExternalRegister Fast external back-end (e.g. for testing)
ext. Oracle / MS SQL / Firebird VirtualTableExternalRegister Fast, secure and industry standard; can be shared outside mORMot
ext. NexusDB VirtualTableExternalRegister The free embedded version let the whole engine be included within your executable, and insertion speed is higher than SQLite3, so it may be a good alternative if your project mostly insert individual objects - using a batch within a transaction let SQlite3 be the faster engine
ext. Jet VirtualTableExternalRegister Could be used as a data exchange format (e.g. with Office applications)
ext. Zeos/FireDAC/UniDAC VirtualTableExternalRegister Allow access to several external engines, with some advantages for Zeos, since direct ZDBC access will by-pass the DB.pas unit and its TDataSet bottleneck - and we will also prefer an active Open Source project!

Whatever database back-end is used, don't forget that mORMot design will allow you to switch from one library to another, just by changing a TSQLDBConnectionProperties class type.
And note that you can mix external engines, on purpose: you are not tied to one single engine, but the database access can be tuned for each ORM table, according to your project needs.

Feedback is welcome on our forum, as usual!