TundraDB - Graph Database Query Language Guide

TundraDB is a high-performance graph database with a custom query language called TundraQL. This guide demonstrates the full feature set with practical examples.

Building TundraDB from Source

If you need to build TundraDB shell from source:

# Clone the repository (if you haven't already)
git clone https://github.com/your-repo/tundradb.git
cd tundradb

# Build in release mode
mkdir -p build_release
cd build_release
cmake -DCMAKE_BUILD_TYPE=Release ..
make -j$(sysctl -n hw.ncpu)

# The binary will be in build_release/tundra_shell

Required dependencies:

ANTLR4 C++ runtime: brew install antlr4-cpp-runtime
Apache Arrow: brew install apache-arrow
spdlog: brew install spdlog
libcds: brew install libcds
gtest: brew install googletest

Google Benchmark:

  git clone https://github.com/google/benchmark.git && \
  cd benchmark && \
  mkdir build && \
  cd build && \
  cmake -DCMAKE_BUILD_TYPE=Release -DBENCHMARK_ENABLE_GTEST_TESTS=OFF .. && \
  make -j && \
  make install && \

TBB: brew install tbb
Java: brew install openjdk@21 then export PATH="/opt/homebrew/opt/openjdk@21/bin:$PATH"

Getting Started

Launch the TundraDB shell:
```
./build_release/tundra_shell
```
or if using the portable version:
```
./tundra_shell_launcher.sh
```

Script Execution: Run TundraQL script files:

# Execute a script and keep shell open
./tundra_shell --script my_script.sql

# Execute script and exit (batch mode)
./tundra_shell --script my_script.sql --detach

# Execute with unique database and output file
./tundra_shell --script my_script.sql --unique-db --output results.txt

Create your schemas and data as shown below, then start querying!

Data Model

Schema Definition

Define the structure of your node types using supported data types:

-- User schema with STRING and INT64 types
CREATE SCHEMA User (name: STRING, age: INT64, department: STRING);

-- Company schema 
CREATE SCHEMA Company (name: STRING, industry: STRING, size: INT64);

-- Project schema
CREATE SCHEMA Project (name: STRING, budget: INT64, status: STRING);

Supported Data Types:

STRING: Text values (e.g., "Alice", "TechCorp")
INT64: Integer values (e.g., 25, 1000)

Note: An id field of type INT64 is automatically added to every schema.

Node Creation

Create nodes with the defined schemas:

-- Create User nodes
CREATE NODE User (name="Alice", age=25, department="Engineering") RETURN id;  -- ID = 0
CREATE NODE User (name="Bob", age=30, department="Engineering") RETURN id;    -- ID = 1
CREATE NODE User (name="Charlie", age=35, department="Marketing") RETURN id;  -- ID = 2
CREATE NODE User (name="David", age=40, department="Engineering") RETURN id;  -- ID = 3

-- Create Company nodes
CREATE NODE Company (name="TechCorp", industry="Technology", size=500) RETURN id;  -- ID = 4
CREATE NODE Company (name="FinanceInc", industry="Finance", size=300) RETURN id;   -- ID = 5

-- Create Project nodes
CREATE NODE Project (name="WebApp", budget=100000, status="Active") RETURN id;     -- ID = 6
CREATE NODE Project (name="MobileApp", budget=150000, status="Active") RETURN id;  -- ID = 7

Important: Node IDs are unique across all node types and start at 0.

Edge Creation

TundraDB offers multiple ways to create edges between nodes:

1. Legacy ID-Based Syntax

-- Create edges using node IDs
CREATE EDGE WORKS_AT FROM User(0) TO Company(4);  -- Alice works at TechCorp
CREATE EDGE WORKS_AT FROM User(1) TO Company(4);  -- Bob works at TechCorp
CREATE EDGE WORKS_AT FROM User(2) TO Company(5);  -- Charlie works at FinanceInc

-- Create friendship relationships
CREATE EDGE FRIEND FROM User(0) TO User(1);  -- Alice is friends with Bob

2. 🆕 Property-Based Node Selection

Select nodes by their properties instead of IDs:

-- Single edge with UNIQUE constraint (fails if multiple matches)
CREATE UNIQUE EDGE WORKS_AT FROM (User{name="Alice"}) TO (Company{name="TechCorp"});

-- Single edge with UNIQUE constraint using multiple properties
CREATE UNIQUE EDGE ASSIGNED_TO FROM (User{name="Bob", department="Engineering"}) 
                                  TO (Project{name="WebApp"});

3. 🆕 Batch Edge Creation

Create multiple edges when properties match multiple nodes:

-- Create edges from ALL Engineering users to TechCorp
CREATE EDGE WORKS_AT FROM (User{department="Engineering"}) TO (Company{name="TechCorp"});
-- Result: Creates 3 edges (Alice, Bob, David → TechCorp)

-- Create edges from ALL Active projects to specific users
CREATE EDGE ASSIGNED_TO FROM (User{name="Alice"}) TO (Project{status="Active"});
-- Result: Creates 2 edges (Alice → WebApp, Alice → MobileApp)

Edge Creation Summary:

Legacy syntax: User(0) - Select by ID
UNIQUE edges: Fail if property selector matches multiple nodes
Batch edges: Create edges to ALL matching nodes
Property matching: Use {property=value} syntax for selection

Committing Changes

Store data persistently:

COMMIT;

Query Language

Basic Node Queries

-- Query all users
MATCH (u:User);

-- Query with specific fields
MATCH (u:User) SELECT u.name, u.age;

-- Query all companies
MATCH (c:Company);

WHERE Clauses

Filter data using various operators:

-- Equality operators
MATCH (u:User) WHERE u.name = "Alice";
MATCH (u:User) WHERE u.age != 30;

-- Comparison operators  
MATCH (u:User) WHERE u.age > 30;
MATCH (u:User) WHERE u.age < 35;

-- String and numeric filtering
MATCH (c:Company) WHERE c.industry = "Technology";
MATCH (p:Project) WHERE p.budget > 100000;

Relationship Queries

Basic Traversals

-- Find users who work at companies
MATCH (u:User)-[:WORKS_AT]->(c:Company);

-- Find users assigned to projects
MATCH (u:User)-[:ASSIGNED_TO]->(p:Project);

-- Find friendships
MATCH (u:User)-[:FRIEND]->(f:User);

Combined Queries

-- Find users at specific companies
MATCH (u:User)-[:WORKS_AT]->(c:Company) 
WHERE c.name = "TechCorp";

-- Find users over 30 who work at tech companies
MATCH (u:User)-[:WORKS_AT]->(c:Company) 
WHERE u.age > 30 AND c.industry = "Technology";

-- Find friends who work at the same company
MATCH (u1:User)-[:FRIEND]->(u2:User), 
      (u1)-[:WORKS_AT]->(c:Company), 
      (u2)-[:WORKS_AT]->(c);

Join Types

TundraQL supports SQL-style joins for relationship queries:

-- INNER join (default) - only matched relationships
MATCH (u:User)-[:WORKS_AT INNER]->(c:Company);

-- LEFT join - all users, even those without companies
MATCH (u:User)-[:WORKS_AT LEFT]->(c:Company);

-- RIGHT join - all companies, even those without users  
MATCH (u:User)-[:WORKS_AT RIGHT]->(c:Company);

-- FULL join - all users and companies
MATCH (u:User)-[:WORKS_AT FULL]->(c:Company);

Join Examples

Given this data setup:

-- Users: Alice(0), Bob(1), Charlie(2), David(3)
-- Companies: TechCorp(4), FinanceInc(5) 
-- Edges: Alice→TechCorp, Bob→TechCorp

INNER JOIN returns only matched relationships:

| u.id | u.name  | c.id | c.name     |
|------|---------|------|------------|
|  0   | "Alice" |  4   | "TechCorp" |
|  1   | "Bob"   |  4   | "TechCorp" |

LEFT JOIN includes all users:

| u.id | u.name    | c.id | c.name     |
|------|-----------|------|------------|
|  0   | "Alice"   |  4   | "TechCorp" |
|  1   | "Bob"     |  4   | "TechCorp" |
|  2   | "Charlie" | null | null       |
|  3   | "David"   | null | null       |

FULL JOIN includes all users and companies:

| u.id | u.name    | c.id | c.name      |
|------|-----------|------|-------------|
|  0   | "Alice"   |  4   | "TechCorp"  |
|  1   | "Bob"     |  4   | "TechCorp"  |
|  2   | "Charlie" | null | null        |
|  3   | "David"   | null | null        |
| null | null      |  5   | "FinanceInc"|

🆕 SHOW Operations

TundraDB provides powerful commands to inspect and monitor your graph data:

Show Edge Types

Display all edge types in the database with their counts:

SHOW EDGE TYPES;

Example Output:

| type      | count |
|-----------|-------|
| WORKS_AT  | 3     |
| FRIEND    | 2     |
| ASSIGNED_TO| 1     |

Total: 3 edge types

Show Edges of Specific Type

View all edges of a particular type with their details:

-- Show all WORKS_AT edges
SHOW EDGES WORKS_AT;

-- Show all FRIEND edges  
SHOW EDGES FRIEND;

-- Show all ASSIGNED_TO edges
SHOW EDGES ASSIGNED_TO;

Example Output:

Edges of type 'WORKS_AT':
| id | source_id | target_id | created_ts    |
|----|-----------|-----------|---------------|
| 0  | 0         | 4         | 1748733662618 |
| 1  | 1         | 4         | 1748733662618 |
| 2  | 2         | 5         | 1748733662618 |

Total: 3 edges

Show Operations Use Cases:

Data Exploration: Understand your graph structure
Debugging: Verify edge creation and deletion
Monitoring: Track edge counts and relationships
Documentation: Generate data summaries

🆕 DELETE Operations

TundraDB supports flexible DELETE operations for both nodes and relationships:

Delete Nodes

Delete by ID

-- Delete specific nodes by ID
DELETE User(0);     -- Delete Alice
DELETE Company(4);  -- Delete TechCorp

Delete by Pattern

-- Delete all nodes of a type
DELETE (u:User);
DELETE (c:Company);

-- Delete specific nodes by pattern
DELETE (u:User) WHERE u.name = "Alice";
DELETE (c:Company) WHERE c.industry = "Technology";

Delete with WHERE Clauses

-- Delete users over a certain age
DELETE (u:User) WHERE u.age > 35;

-- Delete companies with small size
DELETE (c:Company) WHERE c.size < 100;

-- Delete projects with specific status
DELETE (p:Project) WHERE p.status = "Cancelled";

🆕 Delete Edges

TundraDB provides comprehensive edge deletion capabilities with multiple patterns:

Delete All Edges of a Type

-- Delete all WORKS_AT edges
DELETE EDGE WORKS_AT;

-- Delete all FRIEND edges
DELETE EDGE FRIEND;

-- Delete all ASSIGNED_TO edges
DELETE EDGE ASSIGNED_TO;

Delete Outgoing Edges from Specific Nodes

-- Delete all WORKS_AT edges from User(1)
DELETE EDGE WORKS_AT FROM User(1);

-- Delete all FRIEND edges from specific users
DELETE EDGE FRIEND FROM User(0);

-- Using property-based selection
DELETE EDGE WORKS_AT FROM (User{name="Alice"});
DELETE EDGE ASSIGNED_TO FROM (User{department="Marketing"});

Delete Incoming Edges to Specific Nodes

-- Delete all WORKS_AT edges to Company(4)
DELETE EDGE WORKS_AT TO Company(4);

-- Delete all ASSIGNED_TO edges to specific projects
DELETE EDGE ASSIGNED_TO TO Project(6);

-- Using property-based selection
DELETE EDGE WORKS_AT TO (Company{name="TechCorp"});
DELETE EDGE ASSIGNED_TO TO (Project{status="Complete"});

Delete Specific Edges Between Nodes

-- Delete specific edge between two nodes (by ID)
DELETE EDGE WORKS_AT FROM User(0) TO Company(4);
DELETE EDGE FRIEND FROM User(0) TO User(1);

-- Using property-based selection for source and target
DELETE EDGE WORKS_AT FROM (User{name="Alice"}) TO (Company{name="TechCorp"});
DELETE EDGE ASSIGNED_TO FROM (User{department="Engineering"}) TO (Project{name="WebApp"});

-- Mixed ID and property selection
DELETE EDGE WORKS_AT FROM User(1) TO (Company{industry="Technology"});

Edge Deletion Examples

Given this data setup:

-- Edges: 
-- WORKS_AT: Alice→TechCorp, Bob→TechCorp, Charlie→FinanceInc
-- FRIEND: Alice→Bob, Bob→Charlie, Alice→Charlie
-- ASSIGNED_TO: Alice→WebApp, Bob→MobileApp

Delete Pattern Examples:

-- Delete all outgoing FRIEND edges from Alice
DELETE EDGE FRIEND FROM User(0);
-- Result: Removes Alice→Bob and Alice→Charlie (2 edges deleted)

-- Delete all incoming WORKS_AT edges to TechCorp  
DELETE EDGE WORKS_AT TO Company(4);
-- Result: Removes Alice→TechCorp and Bob→TechCorp (2 edges deleted)

-- Delete specific friendship
DELETE EDGE FRIEND FROM User(0) TO User(1);  
-- Result: Removes Alice→Bob (1 edge deleted)

-- Delete all ASSIGNED_TO edges
DELETE EDGE ASSIGNED_TO;
-- Result: Removes all project assignments (2 edges deleted)

Edge Deletion Use Cases:

Relationship Cleanup: Remove outdated or invalid connections
User Management: Delete all relationships when removing users
Data Maintenance: Clean up specific relationship types
Testing: Reset relationship data between test runs

Complete Example Session

Here's a comprehensive example showing TundraDB's full capabilities:

-- 1. Create schemas
CREATE SCHEMA User (name: STRING, age: INT64, department: STRING);
CREATE SCHEMA Company (name: STRING, industry: STRING, size: INT64);
CREATE SCHEMA Project (name: STRING, budget: INT64, status: STRING);

-- 2. Create nodes
CREATE NODE User (name="Alice", age=25, department="Engineering") RETURN id;
CREATE NODE User (name="Bob", age=30, department="Engineering") RETURN id;
CREATE NODE User (name="Charlie", age=35, department="Marketing") RETURN id;

CREATE NODE Company (name="TechCorp", industry="Technology", size=500) RETURN id;
CREATE NODE Company (name="FinanceInc", industry="Finance", size=300) RETURN id;

CREATE NODE Project (name="WebApp", budget=100000, status="Active") RETURN id;
CREATE NODE Project (name="MobileApp", budget=150000, status="Complete") RETURN id;

-- 3. Create relationships using multiple syntaxes
-- Legacy ID-based
CREATE EDGE WORKS_AT FROM User(0) TO Company(3);

-- Property-based with UNIQUE constraint
CREATE UNIQUE EDGE WORKS_AT FROM (User{name="Bob"}) TO (Company{name="TechCorp"});

-- Batch edge creation  
CREATE EDGE ASSIGNED_TO FROM (User{department="Engineering"}) TO (Project{status="Active"});

-- 4. Query examples
-- Basic traversal
MATCH (u:User)-[:WORKS_AT]->(c:Company);

-- Complex filtering
MATCH (u:User)-[:WORKS_AT]->(c:Company) 
WHERE u.age > 25 AND c.industry = "Technology"
SELECT u.name, u.age, c.name;

-- JOIN examples
MATCH (u:User)-[:WORKS_AT LEFT]->(c:Company);

-- 4. Inspect your data
-- Show all edge types and their counts
SHOW EDGE TYPES;

-- View specific edge relationships
SHOW EDGES WORKS_AT;
SHOW EDGES ASSIGNED_TO;

-- 5. Query examples
-- Basic traversal
MATCH (u:User)-[:WORKS_AT]->(c:Company);

-- Complex filtering
MATCH (u:User)-[:WORKS_AT]->(c:Company) 
WHERE u.age > 25 AND c.industry = "Technology"
SELECT u.name, u.age, c.name;

-- JOIN examples
MATCH (u:User)-[:WORKS_AT LEFT]->(c:Company);

-- 6. Advanced edge deletion operations
-- Delete specific edge between nodes
DELETE EDGE WORKS_AT FROM User(0) TO Company(3);

-- Delete all outgoing edges from a user
DELETE EDGE ASSIGNED_TO FROM (User{name="Charlie"});

-- Delete all incoming edges to specific companies
DELETE EDGE WORKS_AT TO (Company{industry="Finance"});

-- Delete all edges of a specific type
DELETE EDGE FRIEND;

-- Verify deletions
SHOW EDGES FRIEND;  -- Should show "No edges found"
SHOW EDGE TYPES;    -- Should show updated counts

-- 5. Cleanup operations
-- Delete completed projects
DELETE (p:Project) WHERE p.status = "Complete";

-- Delete marketing employees
DELETE (u:User) WHERE u.department = "Marketing";

-- Commit changes
COMMIT;

Features Summary

✅ Schema Management: Define typed node structures
✅ Node Operations: Create, query, and delete nodes
✅ Advanced Edge Creation: ID-based, property-based, and batch creation
✅ Flexible Queries: Pattern matching, WHERE clauses, complex traversals
✅ JOIN Support: INNER, LEFT, RIGHT, and FULL joins
✅ SHOW Operations: Inspect edge types and view specific edge relationships
✅ Enhanced DELETE Operations: Comprehensive node and edge deletion patterns
✅ Script Execution: Batch processing and automation
✅ Data Persistence: COMMIT changes to disk

Quick Command Reference

Schema & Node Operations

CREATE SCHEMA User (name: STRING, age: INT64);           -- Define schema
CREATE NODE User (name="Alice", age=25) RETURN id;       -- Create node
MATCH (u:User) WHERE u.age > 30;                        -- Query nodes
DELETE User(0);                                          -- Delete by ID
DELETE (u:User) WHERE u.age > 35;                       -- Delete by pattern

Edge Operations

-- Create edges
CREATE EDGE WORKS_AT FROM User(0) TO Company(3);                    -- By ID
CREATE UNIQUE EDGE WORKS_AT FROM (User{name="Alice"}) TO (Company{name="TechCorp"}); -- By properties
CREATE EDGE WORKS_AT FROM (User{dept="Engineering"}) TO (Company{}); -- Batch creation

-- Query relationships
MATCH (u:User)-[:WORKS_AT]->(c:Company);                -- Basic traversal
MATCH (u:User)-[:WORKS_AT LEFT]->(c:Company);           -- With JOINs

-- Show edge information
SHOW EDGE TYPES;                                         -- List all edge types with counts
SHOW EDGES WORKS_AT;                                     -- Show all edges of specific type

-- Delete edges
DELETE EDGE WORKS_AT;                                    -- Delete all edges of type
DELETE EDGE WORKS_AT FROM User(1);                       -- Delete outgoing edges from node
DELETE EDGE WORKS_AT TO Company(4);                      -- Delete incoming edges to node
DELETE EDGE WORKS_AT FROM User(0) TO Company(3);         -- Delete specific edge
DELETE EDGE WORKS_AT FROM (User{name="Alice"}) TO (Company{name="TechCorp"}); -- Using properties

System Operations

COMMIT;                                                  -- Persist changes to disk

Command Line Options

# Basic usage
./tundra_shell

# Script execution
./tundra_shell --script file.sql                    # Execute script, keep shell open
./tundra_shell -s file.sql --detach                 # Execute and exit
./tundra_shell -s file.sql --unique-db              # Use timestamped database
./tundra_shell -s file.sql --output results.txt     # Save output to file

# Combined options
./tundra_shell -s file.sql -u -o results.txt --detach

TundraDB provides a powerful and intuitive graph database experience with modern query capabilities and flexible data manipulation features.

🚀 Performance Benchmarks

TundraDB delivers high-performance embedded graph database capabilities optimized for gaming workloads.

Test Environment

Hardware: Apple Silicon (M-series)
Data: 1,000,000 users with dynamic properties
Relationships: 500,000 friend connections (50% of users have friends)

Query Performance Results

Simple WHERE Query

SELECT * FROM users WHERE age > 40 AND city = 'NYC'

TundraDB: 7,764 ms (128,800 rows/sec)
SQLite: ~20,000-50,000 rows/sec
PostgreSQL: ~5,000-20,000 rows/sec
Neo4j: ~10,000-50,000 rows/sec

Result: TundraDB is 2-6x faster than traditional embedded databases

Complex Graph Traversal

SELECT f.* FROM users u 
JOIN FRIEND f ON u.id = f.user_id 
WHERE f.age > 50

TundraDB: 14,371 ms (34,800 traversals/sec)
Neo4j: ~20,000-40,000 traversals/sec
ArangoDB: ~5,000-20,000 traversals/sec
OrientDB: ~3,000-15,000 traversals/sec

Result: TundraDB is competitive with established graph databases

Performance Comparison Summary

Database Type	Simple Queries	Graph Traversals	Use Case
TundraDB	128,800/sec	34,800/sec	Gaming/Embedded
SQLite	50,000/sec	N/A	General purpose
PostgreSQL	20,000/sec	N/A	Enterprise
Neo4j	50,000/sec	40,000/sec	Graph analytics
Redis	500,000/sec	N/A	Key-value cache

Gaming Workload Validation

TundraDB easily handles typical gaming database requirements:

Player Queries: 1,000-10,000 QPS ✅ (128K QPS available)
Friend Systems: 100-1,000 QPS ✅ (34K QPS available)
Guild Management: 10-100 QPS ✅ (34K QPS available)
Matchmaking: 1-10 QPS ✅ (34K QPS available)
Real-time Analytics: 1-5 QPS ✅ (34K QPS available)

Key Advantages

✅ Embedded Performance: No network overhead, direct memory access
✅ Graph Capabilities: Native relationship traversal
✅ Schema Flexibility: Dynamic properties without performance penalty
✅ Memory Efficient: Arena-based allocation with string deduplication
✅ Gaming Optimized: Built for real-time, high-throughput workloads

TundraDB delivers enterprise-grade graph database performance in an embedded package, making it ideal for gaming applications that require both high performance and flexible data modeling.

Detailed Benchmark Results

Run on (11 X 23.9999 MHz CPU s)
CPU Caches:
  L1 Data 64 KiB
  L1 Instruction 128 KiB
  L2 Unified 4096 KiB (x11)
Load Average: 2.71, 2.88, 3.41
-------------------------------------------------------------------------------------------------------
Benchmark                                             Time             CPU   Iterations UserCounters...
-------------------------------------------------------------------------------------------------------
tundradb::benchmark::BM_NodeCreation/10             114 us          113 us         4981 bytes_per_second=5.38819Mi/s items_per_second=88.2801k/s
tundradb::benchmark::BM_NodeCreation/100           1052 us         1051 us          675 bytes_per_second=5.8057Mi/s items_per_second=95.1207k/s
tundradb::benchmark::BM_NodeCreation/1000         10320 us        10313 us           68 bytes_per_second=5.91852Mi/s items_per_second=96.969k/s
tundradb::benchmark::BM_NodeCreation/10000       104181 us       104097 us            7 bytes_per_second=5.8633Mi/s items_per_second=96.0644k/s
tundradb::benchmark::BM_FullScan/100               3493 us         3490 us          201 items_per_second=28.6512k/s
tundradb::benchmark::BM_FullScan/1000             38136 us        38034 us           19 items_per_second=26.2921k/s
tundradb::benchmark::BM_FullScan/10000           415585 us       415274 us            2 items_per_second=24.0805k/s
tundradb::benchmark::BM_FullScan/100000         4273620 us      4266754 us            1 items_per_second=23.437k/s
tundradb::benchmark::BM_SimpleJoin/100             6122 us         6117 us          114 items_per_second=16.3468k/s
tundradb::benchmark::BM_SimpleJoin/1000           61735 us        61688 us           11 items_per_second=16.2107k/s
tundradb::benchmark::BM_SimpleJoin/10000         663975 us       654214 us            1 items_per_second=15.2855k/s
tundradb::benchmark::BM_ComplexJoin/100           12351 us        12341 us           57 items_per_second=8.10276k/s
tundradb::benchmark::BM_ComplexJoin/1000         131668 us       131570 us            5 items_per_second=7.60053k/s
tundradb::benchmark::BM_ComplexJoin/5000         696019 us       695514 us            1 items_per_second=7.18893k/s
tundradb::benchmark::BM_FilteredQuery/100          1892 us         1890 us          371 items_per_second=52.9014k/s
tundradb::benchmark::BM_FilteredQuery/1000        18054 us        18042 us           39 items_per_second=55.4269k/s
tundradb::benchmark::BM_FilteredQuery/10000      208273 us       208133 us            3 items_per_second=48.0463k/s
tundradb::benchmark::BM_FilteredQuery/100000    2233684 us      2231174 us            1 items_per_second=44.8195k/s

Name		Name	Last commit message	Last commit date
Latest commit History 202 Commits
.devcontainer		.devcontainer
.github/workflows		.github/workflows
Formula		Formula
antlr		antlr
include		include
libs		libs
scripts		scripts
src		src
test_scripts		test_scripts
tests		tests
.clang-format		.clang-format
.clang-tidy		.clang-tidy
.gitignore		.gitignore
CMakeLists.txt		CMakeLists.txt
DELETE_SYNTAX.md		DELETE_SYNTAX.md
DISTRIBUTION.md		DISTRIBUTION.md
Dockerfile		Dockerfile
MEMORY_NODE_ARENA.md		MEMORY_NODE_ARENA.md
README.md		README.md
SCRIPT_EXECUTION_FEATURE.md		SCRIPT_EXECUTION_FEATURE.md
TEST.MD		TEST.MD
benchmark.md		benchmark.md
check-code-quality.sh		check-code-quality.sh
format-code.sh		format-code.sh
parse_sample.py		parse_sample.py

dmgcodevil/tundradb

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