DBMS > Databend vs. HEAVY.AI vs. Microsoft Azure Cosmos DB vs. TinkerGraph

System Properties Comparison Databend vs. HEAVY.AI vs. Microsoft Azure Cosmos DB vs. TinkerGraph

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Globally distributed, horizontally scalable, multi-model database service

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

github.com/datafuselabs/databend
www.databend.com

github.com/heavyai/heavydb
www.heavy.ai

azure.microsoft.com/services/cosmos-db

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

docs.databend.com

docs.heavy.ai

learn.microsoft.com/azure/cosmos-db

Developer

Databend Labs

HEAVY.AI, Inc.

Microsoft

Initial release

2021

2016

2014

2009

Current release

1.0.59, April 2023

5.10, January 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

Apache 2.0

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++ and CUDA

Java

Server operating systems

hosted
Linux
macOS

Linux

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

JDBC
ODBC
Thrift
Vega

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

TinkerPop 3

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Groovy
Java

Server-side scripts

Stored procedures

JavaScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

yes

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.