DBMS > CockroachDB vs. Google BigQuery vs. Qdrant vs. TigerGraph

System Properties Comparison CockroachDB vs. Google BigQuery vs. Qdrant vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Large scale data warehouse service with append-only tables

A high-performance vector database with neural network or semantic-based matching

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Relational DBMS

Vector DBMS

Graph DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

www.cockroachlabs.com

cloud.google.com/bigquery

github.com/qdrant/qdrant
qdrant.tech

www.tigergraph.com

Technical documentation

www.cockroachlabs.com/docs

cloud.google.com/bigquery/docs

qdrant.tech/documentation

docs.tigergraph.com

Developer

Cockroach Labs

Google

Qdrant

Initial release

2015

2010

2021

2017

Current release

24.1.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Rust

C++

Server operating systems

Linux
macOS
Windows

hosted

Docker
Linux
macOS
Windows

Linux

Data scheme

dynamic schema

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes, wire compatible with PostgreSQL

yes

SQL-like query language (GSQL)

APIs and other access methods

JDBC

RESTful HTTP/JSON API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

C++
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Role-based access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Key-based authentication

Role-based access control

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