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Users don't think about replicas. They don't care about network partitions. They certainly don't understand vector clocks. They have one expectation: the system should work like a single computer.
When a user updates their profile and immediately views it, they expect to see the update. When they withdraw money and check their balance, they expect it to reflect the withdrawal. When they post a message and scroll back, they expect it to still be there.
This expectation—that a user's view of the system should be coherent and non-surprising—is what session consistency provides. It's not global strong consistency (other users may see different things), but within the boundary of a single user's session, the system behaves as if there's only one copy of data, updated atomically, with no time travel.
Session consistency is the art of providing the illusion of simplicity atop the reality of distribution. It's achieved by combining four complementary guarantees: Read Your Writes, Monotonic Reads, Monotonic Writes, and Writes Follow Reads. Together, they create a coherent user experience that builds trust and prevents confusion.
By the end of this page, you will understand the four session guarantees and how they combine, how to implement session consistency with version vectors and tokens, the difference between session consistency and strong consistency, how to define and manage session boundaries, cross-session scenarios and their handling, and production implementations in Azure Cosmos DB, MongoDB, and other systems.
Session consistency was formalized by Terry, Demers, Petersen, Spreitzer, Theimer, and Welch in their 1994 paper "Session Guarantees for Weakly Consistent Replicated Data." They identified four complementary guarantees that together provide intuitive per-client consistency:
1. Read Your Writes (RYW) A read following a write (in the same session) will reflect that write or a subsequent one. Prevents: User updates profile, refreshes, sees old profile.
2. Monotonic Reads (MR) Once a client has seen a particular version of data, subsequent reads will never return an older version. Prevents: User sees message count of 10, refreshes, sees 8.
3. Monotonic Writes (MW) Writes by a session are applied in the order they were issued. Prevents: User posts "Hello" then "World"; observers see "World" without "Hello".
4. Writes Follow Reads (WFR) A write following a read will be applied to a state that includes the effects of the values that were read. Prevents: User replies to a message that becomes invisible to them afterward.
| Guarantee | Formal Statement | Intuition |
|---|---|---|
| RYW | W(x,v) → R(x) ⟹ R(x) returns v or later | See what you wrote |
| MR | R(x)→v₁ → R(x)→v₂ ⟹ v₂.version ≥ v₁.version | Never go backward |
| MW | W(x,v₁) → W(x,v₂) ⟹ v₁ applied before v₂ | Writes ordered |
| WFR | R(x)→v → W(y,u) ⟹ W observes v | Writes see prior reads |
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# Session Guarantees: Formal Model and Violation Detectionfrom dataclasses import dataclass, fieldfrom typing import Dict, List, Optional, Set, Tuplefrom enum import Enum class OperationType(Enum): READ = "read" WRITE = "write" @dataclassclass Operation: """A single operation in a session.""" op_type: OperationType key: str value: Optional[any] # For writes observed_version: Optional[int] # For reads: version that was returned written_version: Optional[int] # For writes: version that was created timestamp: float @dataclassclass SessionHistory: """Record of operations in a session for guarantee checking.""" operations: List[Operation] = field(default_factory=list) # Tracking state last_read_versions: Dict[str, int] = field(default_factory=dict) # key -> version last_write_versions: Dict[str, int] = field(default_factory=dict) # key -> version def add_read(self, key: str, observed_version: int, timestamp: float): """Record a read operation.""" op = Operation( op_type=OperationType.READ, key=key, value=None, observed_version=observed_version, written_version=None, timestamp=timestamp ) self.operations.append(op) # Check monotonic reads if key in self.last_read_versions: if observed_version < self.last_read_versions[key]: raise MonotonicReadsViolation( f"Read version {observed_version} < prior {self.last_read_versions[key]}" ) # Check read-your-writes if key in self.last_write_versions: if observed_version < self.last_write_versions[key]: raise ReadYourWritesViolation( f"Read version {observed_version} < written {self.last_write_versions[key]}" ) self.last_read_versions[key] = max( self.last_read_versions.get(key, 0), observed_version ) def add_write(self, key: str, value: any, written_version: int, timestamp: float, observed_context: Dict[str, int]): """ Record a write operation. Args: observed_context: Versions that were visible when write was issued (for writes-follow-reads checking) """ op = Operation( op_type=OperationType.WRITE, key=key, value=value, observed_version=None, written_version=written_version, timestamp=timestamp ) self.operations.append(op) # Check monotonic writes if key in self.last_write_versions: if written_version <= self.last_write_versions[key]: raise MonotonicWritesViolation( f"Write version {written_version} not > prior {self.last_write_versions[key]}" ) # Check writes-follow-reads (system must have applied based on observed context) for read_key, read_version in observed_context.items(): if read_key in self.last_read_versions: if self.last_read_versions[read_key] > read_version: raise WritesFollowReadsViolation( f"Write context has {read_key}@{read_version}, " f"but we read {self.last_read_versions[read_key]}" ) self.last_write_versions[key] = written_version class MonotonicReadsViolation(Exception): """Raised when monotonic reads guarantee is violated.""" pass class ReadYourWritesViolation(Exception): """Raised when read-your-writes guarantee is violated.""" pass class MonotonicWritesViolation(Exception): """Raised when monotonic writes guarantee is violated.""" pass class WritesFollowReadsViolation(Exception): """Raised when writes-follow-reads guarantee is violated.""" pass # ════════════════════════════════════════════════════════════════════# Demonstration: Violation Scenarios# ════════════════════════════════════════════════════════════════════ def demonstrate_violations(): """ Show examples of each guarantee violation. These are the scenarios session consistency prevents. """ # Scenario 1: Monotonic Reads Violation print("=== Monotonic Reads Violation ===") history = SessionHistory() history.add_read("profile", observed_version=5, timestamp=1.0) try: history.add_read("profile", observed_version=3, timestamp=2.0) # Went backward! except MonotonicReadsViolation as e: print(f"Caught: {e}") # Scenario 2: Read-Your-Writes Violation print("=== Read-Your-Writes Violation ===") history2 = SessionHistory() history2.add_write("profile", {"name": "Alice"}, written_version=10, timestamp=1.0, observed_context={}) try: history2.add_read("profile", observed_version=8, timestamp=2.0) # Didn't see write! except ReadYourWritesViolation as e: print(f"Caught: {e}") # Scenario 3: Monotonic Writes Violation print("=== Monotonic Writes Violation ===") history3 = SessionHistory() history3.add_write("counter", 1, written_version=5, timestamp=1.0, observed_context={}) try: history3.add_write("counter", 2, written_version=3, timestamp=2.0) # Out of order! except MonotonicWritesViolation as e: print(f"Caught: {e}")Each guarantee prevents a specific class of anomaly. Missing any one creates a gap in user experience. RYW without MR: user sees their update, then sees an older version on next page load. MW without WFR: writes are ordered, but may be based on stale reads. The four guarantees are complementary and together provide comprehensive per-session coherence.
Session consistency is implemented by tracking the logical position of what each session has observed and ensuring subsequent operations respect that position.
Core Concept: Observation Tracking
Maintain, for each session, a record of:
Every operation checks against and updates this record.
Implementation Components:
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# Complete Session Consistency Implementationfrom dataclasses import dataclass, fieldfrom typing import Dict, List, Optional, Tupleimport timeimport jsonimport base64 @dataclassclass SessionState: """ Complete state for a client session. Combines all four session guarantee requirements. """ session_id: str # Read tracking (for MR + RYW) observed_reads: Dict[str, int] = field(default_factory=dict) # key -> max version seen # Write tracking (for RYW + MW) written_versions: Dict[str, int] = field(default_factory=dict) # key -> version written # Global position (for cross-key consistency) global_position: int = 0 # Write order tracking (for MW) pending_writes: List[str] = field(default_factory=list) # write IDs in order def minimum_acceptable_version(self, key: str) -> int: """ Minimum version acceptable for a read on this key. Satisfies both RYW (must see own writes) and MR (must not go backward). """ ryw_requirement = self.written_versions.get(key, 0) mr_requirement = self.observed_reads.get(key, 0) return max(ryw_requirement, mr_requirement) def record_read(self, key: str, version: int): """Update state after a read operation.""" current_max = self.observed_reads.get(key, 0) self.observed_reads[key] = max(current_max, version) self.global_position = max(self.global_position, version) def record_write(self, key: str, version: int, write_id: str): """Update state after a write operation.""" self.written_versions[key] = version self.observed_reads[key] = max( self.observed_reads.get(key, 0), version ) self.global_position = max(self.global_position, version) self.pending_writes.append(write_id) def get_write_context(self) -> Dict[str, int]: """ Get context for writes-follow-reads. This context must be respected by the server when applying the write. """ return { **self.observed_reads, **{k: v for k, v in self.written_versions.items()} } def serialize(self) -> str: """Serialize for transmission/storage.""" data = { "sid": self.session_id, "reads": self.observed_reads, "writes": self.written_versions, "pos": self.global_position } return base64.b64encode(json.dumps(data).encode()).decode() @classmethod def deserialize(cls, token: str) -> 'SessionState': """Restore from serialized form.""" data = json.loads(base64.b64decode(token)) state = cls(session_id=data["sid"]) state.observed_reads = data.get("reads", {}) state.written_versions = data.get("writes", {}) state.global_position = data.get("pos", 0) return state class SessionConsistentStore: """ Store providing full session consistency guarantees. """ def __init__(self, replicas: List['Replica']): self.replicas = replicas self.primary = replicas[0] # Convention: first replica is primary def read(self, session: SessionState, key: str) -> Tuple[any, int]: """ Read with session consistency guarantees. Returns: (value, version) Raises: ConsistencyError if no replica can satisfy requirements """ min_version = session.minimum_acceptable_version(key) # Try replicas in order of freshness for replica in self._order_by_freshness(): value, version = replica.read_versioned(key) if version >= min_version: session.record_read(key, version) return value, version # No replica fresh enough - try blocking read from primary value, version = self.primary.read_blocking(key, min_version, timeout=5.0) if version >= min_version: session.record_read(key, version) return value, version raise ConsistencyError( f"Cannot satisfy session requirement: need version >= {min_version}" ) def write(self, session: SessionState, key: str, value: any) -> int: """ Write with session consistency guarantees. Ensures: - Monotonic writes (new version > session's last write to this key) - Writes follow reads (write context includes observed reads) Returns: version of the write """ # Build context for writes-follow-reads context = session.get_write_context() # Generate write ID for ordering write_id = f"{session.session_id}:{time.time_ns()}" # Execute write on primary with context version = self.primary.write_with_context(key, value, context, write_id) # Verify monotonic writes if key in session.written_versions: if version <= session.written_versions[key]: raise ConsistencyError( f"Monotonic write violation: {version} <= {session.written_versions[key]}" ) session.record_write(key, version, write_id) return version def read_multiple(self, session: SessionState, keys: List[str]) -> Dict[str, Tuple[any, int]]: """ Read multiple keys with consistent session view. All reads will be from the same snapshot that satisfies session requirements for all keys. """ # Find minimum global position needed min_global = session.global_position for key in keys: min_global = max(min_global, session.minimum_acceptable_version(key)) # Find a replica that can satisfy all requirements for replica in self._order_by_freshness(): if replica.current_position >= min_global: results = {} for key in keys: value, version = replica.read_versioned(key) results[key] = (value, version) session.record_read(key, version) return results raise ConsistencyError(f"No replica at position >= {min_global}") def _order_by_freshness(self) -> List['Replica']: """Order replicas by current position (freshest first).""" return sorted(self.replicas, key=lambda r: -r.current_position) class Replica: """A database replica with versioned data.""" def __init__(self, replica_id: str, is_primary: bool = False): self.id = replica_id self.is_primary = is_primary self.data: Dict[str, Tuple[any, int]] = {} # key -> (value, version) self.current_position: int = 0 self.write_order: List[str] = [] # Ordered write IDs def read_versioned(self, key: str) -> Tuple[any, int]: """Read value and its version.""" if key in self.data: return self.data[key] return None, 0 def read_blocking(self, key: str, min_version: int, timeout: float) -> Tuple[any, int]: """Read, blocking until min_version is available.""" deadline = time.time() + timeout while time.time() < deadline: value, version = self.read_versioned(key) if version >= min_version: return value, version time.sleep(0.01) return self.read_versioned(key) def write_with_context(self, key: str, value: any, context: Dict[str, int], write_id: str) -> int: """ Execute write respecting session context. The context ensures writes-follow-reads by requiring that the current state includes all versions the client observed. """ # Verify context is satisfied for ctx_key, ctx_version in context.items(): current = self.data.get(ctx_key, (None, 0))[1] if current < ctx_version: # Context not satisfied - would violate writes-follow-reads # In practice, this might block or fail raise ConsistencyError( f"Context violation: {ctx_key} at {current} < required {ctx_version}" ) # Apply write self.current_position += 1 self.data[key] = (value, self.current_position) self.write_order.append(write_id) return self.current_position class ConsistencyError(Exception): """Raised when session consistency cannot be satisfied.""" passA critical design decision: what defines a session?
Too narrow (each request is a session) → no cross-request guarantees. Too broad (all requests from a user forever) → state becomes massive.
The right boundary depends on application semantics:
1. Connection-Based Sessions Session = database connection. Natural for connection-pooled applications. Problem: Connection pools share connections across requests.
2. Request-Based Sessions Session = single HTTP request. No cross-request state needed. Problem: Multi-step operations have no guarantees.
3. Authentication-Based Sessions Session = logged-in user session. Matches user mental model. Problem: Long sessions accumulate state; multi-device complications.
4. Transaction-Based Sessions Session = explicit transaction boundary. Problem: Requires application-level transaction management.
5. Token-Based Sessions Session travels with the client via token. Most flexible. Problem: Token size grows; token can be lost.
| Strategy | Pros | Cons | Use Case |
|---|---|---|---|
| Connection | Simple, automatic | Pooling breaks it | Direct DB access |
| Request | No state management | No cross-request | Stateless APIs |
| Auth Session | Matches UX | Long sessions grow | Web applications |
| Transaction | Explicit scope | Requires management | Complex workflows |
| Token | Flexible, portable | Token maintenance | Distributed clients |
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# Session Boundary Management Strategiesfrom dataclasses import dataclass, fieldfrom typing import Optional, Dictfrom datetime import datetime, timedeltaimport threading # ════════════════════════════════════════════════════════════════════# Strategy 1: Connection-Based Sessions# ════════════════════════════════════════════════════════════════════ class ConnectionSession: """ Session tied to database connection. Used by traditional database drivers. """ # Thread-local storage for session per connection _local = threading.local() @classmethod def get_or_create(cls, connection) -> SessionState: """Get session for current connection.""" if not hasattr(cls._local, 'sessions'): cls._local.sessions = {} conn_id = id(connection) if conn_id not in cls._local.sessions: cls._local.sessions[conn_id] = SessionState( session_id=f"conn-{conn_id}" ) return cls._local.sessions[conn_id] @classmethod def clear(cls, connection): """Clear session when connection returns to pool.""" if hasattr(cls._local, 'sessions'): cls._local.sessions.pop(id(connection), None) # ════════════════════════════════════════════════════════════════════# Strategy 2: Token-Based Sessions with Lifecycle Management# ════════════════════════════════════════════════════════════════════ @dataclassclass ManagedSession: """Session with lifecycle metadata.""" state: SessionState created_at: datetime last_access: datetime access_count: int = 0 def is_expired(self, max_age: timedelta, max_idle: timedelta) -> bool: """Check if session should be expired.""" now = datetime.now() if now - self.created_at > max_age: return True # Absolute expiration if now - self.last_access > max_idle: return True # Idle expiration return False class TokenSessionManager: """ Manages token-based sessions with lifecycle policies. """ def __init__(self, max_age: timedelta = timedelta(hours=24), max_idle: timedelta = timedelta(hours=1), max_state_size: int = 10000): # Max keys tracked self.max_age = max_age self.max_idle = max_idle self.max_state_size = max_state_size self.sessions: Dict[str, ManagedSession] = {} def create_session(self) -> str: """Create new session, return token.""" import uuid session_id = str(uuid.uuid4()) state = SessionState(session_id=session_id) self.sessions[session_id] = ManagedSession( state=state, created_at=datetime.now(), last_access=datetime.now() ) return state.serialize() def get_session(self, token: str) -> Optional[SessionState]: """Restore session from token.""" try: state = SessionState.deserialize(token) except: return None session_id = state.session_id if session_id in self.sessions: managed = self.sessions[session_id] # Check expiration if managed.is_expired(self.max_age, self.max_idle): del self.sessions[session_id] return None # Update access time managed.last_access = datetime.now() managed.access_count += 1 # Merge token state with server state (client might have fresher info) managed.state = self._merge_states(managed.state, state) return managed.state else: # Session not on server - validate and accept token state if self._validate_token(state): self.sessions[session_id] = ManagedSession( state=state, created_at=datetime.now(), last_access=datetime.now() ) return state return None def update_session(self, state: SessionState) -> str: """Update session and return new token.""" session_id = state.session_id if session_id in self.sessions: self.sessions[session_id].state = state self.sessions[session_id].last_access = datetime.now() # Compact state if too large if self._state_size(state) > self.max_state_size: state = self._compact_state(state) return state.serialize() def _merge_states(self, server: SessionState, client: SessionState) -> SessionState: """Merge server and client states (point-wise maximum).""" merged = SessionState(session_id=server.session_id) all_keys = set(server.observed_reads.keys()) | set(client.observed_reads.keys()) for key in all_keys: merged.observed_reads[key] = max( server.observed_reads.get(key, 0), client.observed_reads.get(key, 0) ) all_keys = set(server.written_versions.keys()) | set(client.written_versions.keys()) for key in all_keys: merged.written_versions[key] = max( server.written_versions.get(key, 0), client.written_versions.get(key, 0) ) merged.global_position = max(server.global_position, client.global_position) return merged def _state_size(self, state: SessionState) -> int: """Estimate state size (number of tracked keys).""" return len(state.observed_reads) + len(state.written_versions) def _compact_state(self, state: SessionState) -> SessionState: """ Reduce state size by removing old entries. Trades precision for size. May require fallback to stronger reads. """ # Keep only global position, drop per-key tracking compacted = SessionState(session_id=state.session_id) compacted.global_position = state.global_position return compacted def _validate_token(self, state: SessionState) -> bool: """Validate token hasn't been tampered with.""" # In production: verify HMAC or signature return TrueMajor distributed databases implement session consistency with varying mechanisms and guarantees:
| System | Implementation | Guarantees | Notes |
|---|---|---|---|
| Azure Cosmos DB | Session tokens with LSN per partition | All four guarantees | Default consistency level; SDK handles automatically |
| MongoDB | Causal sessions with cluster time | All four via causally consistent sessions | Requires readConcern: majority |
| DynamoDB | Application-level with version attributes | RYW via strongly consistent reads | No native session abstraction |
| Cassandra | Lightweight transactions + quorum | Partial (QUORUM provides RYW) | No native session tokens |
| CockroachDB | Strong consistency by default | Exceeds session guarantees | Session guarantees are subset of strong |
| Spanner | TrueTime + strong consistency | Exceeds session guarantees | Global strong consistency |
Cosmos DB's session token contains: partition key ranges, LSNs per partition, and global commit timestamp. When you read or write, the SDK captures the response token. On subsequent requests, it sends this token, and the server ensures the replica has reached at least that position before responding. If the contacted replica is behind, Cosmos either waits or redirects to a fresher replica.
Session consistency explicitly does not guarantee consistency between different sessions. This creates scenarios applications must handle:
Scenario 1: Alice and Bob Collaboration Alice updates a document. Bob, in a different session, may not see the update immediately.
Scenario 2: Multi-Device User User edits on phone, then checks laptop—two different sessions.
Scenario 3: Microservice Communication Service A writes to DB, calls Service B, which reads from DB—may not see A's write.
Scenario 4: Long-Running Sessions Session state grows unbounded, token becomes huge.
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# Patterns for Cross-Session Consistency # ════════════════════════════════════════════════════════════════════# Pattern 1: Session Token Propagation for Microservices# ════════════════════════════════════════════════════════════════════ class SessionPropagatingClient: """ HTTP client that propagates session tokens between services. Ensures cross-service session consistency. """ SESSION_TOKEN_HEADER = "X-Session-Token" def __init__(self, base_url: str): self.base_url = base_url self.session_token: Optional[str] = None def set_session_token(self, token: str): """Set token received from upstream service.""" self.session_token = token def get_session_token(self) -> Optional[str]: """Get token to pass to downstream services.""" return self.session_token def request(self, method: str, path: str, **kwargs) -> dict: """Make request with session token propagation.""" headers = kwargs.get('headers', {}) # Include session token if we have one if self.session_token: headers[self.SESSION_TOKEN_HEADER] = self.session_token kwargs['headers'] = headers response = self._do_request(method, path, **kwargs) # Capture session token from response if self.SESSION_TOKEN_HEADER in response.headers: self.session_token = response.headers[self.SESSION_TOKEN_HEADER] return response # ════════════════════════════════════════════════════════════════════# Pattern 2: User-Scoped Sessions for Multi-Device# ════════════════════════════════════════════════════════════════════ class UserScopedSessionStore: """ Store sessions keyed by user ID rather than device/connection. Provides cross-device session consistency. """ def __init__(self, cache_client): self.cache = cache_client # e.g., Redis def get_session(self, user_id: str) -> SessionState: """Get or create session for user (not device).""" cached = self.cache.get(f"session:{user_id}") if cached: return SessionState.deserialize(cached) # New session for user state = SessionState(session_id=f"user-{user_id}") self.cache.set(f"session:{user_id}", state.serialize()) return state def update_session(self, user_id: str, state: SessionState): """Update user's session (atomic CAS to handle concurrent updates).""" key = f"session:{user_id}" for _ in range(3): # Retry on conflict current = self.cache.get(key) if current: current_state = SessionState.deserialize(current) # Merge to handle concurrent device updates merged = self._merge(current_state, state) if self.cache.cas(key, current, merged.serialize()): return else: if self.cache.setnx(key, state.serialize()): return raise Exception("Failed to update session after retries") # ════════════════════════════════════════════════════════════════════# Pattern 3: Hybrid Consistency for Critical Paths# ════════════════════════════════════════════════════════════════════ class HybridConsistencyStore: """ Uses session consistency by default, strong consistency for critical paths. Balances performance with correctness requirements. """ def __init__(self, db_client): self.db = db_client self.session = SessionState(session_id="hybrid") def read_session(self, key: str) -> any: """Read with session consistency (default).""" return self.db.read(key, session_token=self.session.serialize()) def read_strong(self, key: str) -> any: """Read with strong consistency (critical paths).""" value = self.db.read_strong(key) # Quorum read # Update session to reflect this strong read self.session.record_read(key, self.db.get_current_version(key)) return value def write_session(self, key: str, value: any): """Write with session consistency (default).""" version = self.db.write(key, value, session_token=self.session.serialize()) self.session.record_write(key, version, f"w-{time.time_ns()}") def write_strong(self, key: str, value: any): """Write with strong consistency (critical paths).""" version = self.db.write_strong(key, value) # Quorum write self.session.record_write(key, version, f"w-{time.time_ns()}")If your UI shows Alice's updates to Bob, you're implicitly claiming cross-session consistency. Users will expect it to work reliably. Either provide strong consistency for cross-user features, or set expectations with 'last synced' indicators, refresh buttons, and graceful handling of stale data.
Congratulations! You've completed the Consistency Models Overview module, covering the full spectrum from strong to eventual consistency. You understand linearizability, eventual consistency with CRDTs, causal ordering with vector clocks, read-your-writes guarantees, and session consistency combining all four session guarantees. You're now equipped to make informed consistency model decisions for any distributed system design. Continue to Module 2: Strong Consistency for implementation deep dives, or Module 5: Conflict Resolution Strategies.