Synapse's database schema is stored in the
Synapse supports splitting its datastore across multiple physical databases (which can be useful for large installations), and the schema files are therefore split according to the logical database they apply to.
At the time of writing, the following "logical" databases are supported:
state- used to store Matrix room state (more specifically,
state_groups, their relationships and contents).
main- stores everything else.
common directory contains schema files for tables which must be
present on all physical databases.
Synapse manages its database schema via "schema versions". These are mainly used to help avoid confusion if the Synapse codebase is rolled back after the database is updated. They work as follows:
The Synapse codebase defines a constant
synapse.storage.schema.SCHEMA_VERSIONwhich represents the expectations made about the database by that version. For example, as of Synapse v1.36, this is
The database stores a "compatibility version" in
schema_compat_version.compat_versionwhich defines the
SCHEMA_VERSIONof the oldest version of Synapse which will work with the database. On startup, if
compat_versionis found to be newer than
SCHEMA_VERSION, Synapse will refuse to start.
Synapse automatically updates this field from
Whenever a backwards-incompatible change is made to the database format (normally via a
synapse.storage.schema.SCHEMA_COMPAT_VERSIONis also updated so that administrators can not accidentally roll back to a too-old version of Synapse.
Generally, the goal is to maintain compatibility with at least one or two previous releases of Synapse, so any substantial change tends to require multiple releases and a bit of forward-planning to get right.
As a worked example: we want to remove the
room_stats_historical table. Here is how it
might pan out.
Replace any code that reads from
room_stats_historicalwith alternative implementations, but keep writing to it in case of rollback to an earlier version. Also, increase
synapse.storage.schema.SCHEMA_VERSION. In this instance, there is no existing code which reads from
room_stats_historical, so our starting point is:
Next (say in Synapse v1.37.0): remove the code that writes to
room_stats_historical, but don’t yet remove the table in case of rollback to v1.36.0. Again, we increase
synapse.storage.schema.SCHEMA_VERSION, but because we have not broken compatibility with v1.36, we do not yet update
SCHEMA_COMPAT_VERSION. We now have:
Later (say in Synapse v1.38.0): we can remove the table altogether. This will break compatibility with v1.36.0, so we must update
SCHEMA_COMPAT_VERSIONaccordingly. There is no need to update
synapse.storage.schema.SCHEMA_VERSION, since there is no change to the Synapse codebase here. So we end up with:
If in doubt about whether to update
SCHEMA_VERSION or not, it is generally best to
lean towards doing so.
full_schemas directories, only the most recently-numbered snapshot is used
54 at the time of writing). Older snapshots (eg,
16) are present for historical
If you want to recreate these schemas, they need to be made from a database that has had all background updates run.
To do so, use
scripts-dev/make_full_schema.sh. This will produce new
Ensure postgres is installed, then run:
./scripts-dev/make_full_schema.sh -p postgres_username -o output_dir/
NB at the time of writing, this script predates the split into separate
databases so will require updates to handle that correctly.
Delta files define the steps required to upgrade the database from an earlier version. They can be written as either a file containing a series of SQL statements, or a Python module.
Synapse remembers which delta files it has applied to a database (they are stored in the
applied_schema_deltas table) and will not re-apply them (even if a given file is
Delta files should be placed in a directory named
They are applied in alphanumeric order, so by convention the first two characters
of the filename should be an integer such as
01, to put the file in the right order.
These should be named
*.sql, or — for changes which should only be applied for a
given database engine —
*.sql.sqlite. For example, a delta which
adds a new column to the
foo table might be called
Note that our SQL parser is a bit simple - it understands comments (
but complex statements which require a
; in the middle of them (such as
CREATE TRIGGER) are beyond it and you'll have to use a Python delta file.
For more flexibility, a delta file can take the form of a python module. These should
*.py. Note that database-engine-specific modules are not supported here –
instead you can write
if isinstance(database_engine, PostgresEngine) or similar.
A Python delta module should define either or both of the following functions:
import synapse.config.homeserver import synapse.storage.engines import synapse.storage.types def run_create( cur: synapse.storage.types.Cursor, database_engine: synapse.storage.engines.BaseDatabaseEngine, ) -> None: """Called whenever an existing or new database is to be upgraded""" ... def run_upgrade( cur: synapse.storage.types.Cursor, database_engine: synapse.storage.engines.BaseDatabaseEngine, config: synapse.config.homeserver.HomeServerConfig, ) -> None: """Called whenever an existing database is to be upgraded.""" ...
Boolean columns require special treatment, since SQLite treats booleans the same as integers.
There are three separate aspects to this:
Any new boolean column must be added to the
synapse/_scripts/synapse_port_db.py. This tells the port script to cast the integer value from SQLite to a boolean before writing the value to the postgres database.
Before SQLite 3.23,
FALSEwere not recognised as constants by SQLite, and the
IS [NOT] TRUE/
IS [NOT] FALSEoperators were not supported. This makes it necessary to avoid using
FALSEconstants in SQL commands.
For example, to insert a
TRUEvalue into the database, write:
txn.execute("INSERT INTO tbl(col) VALUES (?)", (True, ))
Default values for new boolean columns present a particular difficulty. Generally it is best to create separate schema files for Postgres and SQLite. For example:
# in 00delta.sql.postgres: ALTER TABLE tbl ADD COLUMN col BOOLEAN DEFAULT FALSE;
# in 00delta.sql.sqlite: ALTER TABLE tbl ADD COLUMN col BOOLEAN DEFAULT 0;
Note that there is a particularly insidious failure mode here: the Postgres flavour will be accepted by SQLite 3.22, but will give a column whose default value is the string
"FALSE"- which, when cast back to a boolean in Python, evaluates to
event_id's can be considered globally unique although there has been a lot of
debate on this topic in places like
has no resolution yet (as of 2022-09-01). There are several places in Synapse
and even in the Matrix APIs like
where we assume that event IDs are globally unique.
event_id in a database schema, it is often nice to accompany it
PRIMARY KEY (room_id, event_id) and a
FOREIGN KEY(room_id) REFERENCES rooms(room_id)) which makes flexible lookups easy. For example it
makes it very easy to find and clean up everything in a room when it needs to be
purged (no need to use sub-
select query or join from the
A note on collisions: In room versions
2 it's possible to end up with
two events with the same
event_id (in the same or different rooms). After room
3, that can only happen with a hash collision, which we basically hope
will never happen (SHA256 has a massive big key space).