DBMS > Dgraph vs. LevelDB vs. Microsoft Azure Cosmos DB vs. TDengine vs. Warp 10

System Properties Comparison Dgraph vs. LevelDB vs. Microsoft Azure Cosmos DB vs. TDengine vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Globally distributed, horizontally scalable, multi-model database service

Time Series DBMS and big data platform

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Graph DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

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

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

dgraph.io

github.com/google/leveldb

azure.microsoft.com/services/cosmos-db

github.com/taosdata/TDengine
tdengine.com

www.warp10.io

Technical documentation

dgraph.io/docs

github.com/google/leveldb/blob/main/doc/index.md

learn.microsoft.com/azure/cosmos-db

docs.tdengine.com

www.warp10.io/content/02_Getting_started

Developer

Dgraph Labs, Inc.

Google

Microsoft

TDEngine, previously Taos Data

SenX

Initial release

2016

2011

2014

2019

2015

Current release

1.23, February 2021

3.0, August 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

commercial

Open Source

AGPL V3, also commercial editions available

Open Source

Apache License 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

C++

Java

Server operating systems

Linux
OS X
Windows

Illumos
Linux
OS X
Windows

hosted

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

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

SQL-like query language

Standard SQL with extensions for time-series applications

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

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

JDBC
RESTful HTTP API

HTTP API
Jupyter
WebSocket

Supported programming languages

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

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

Server-side scripts

Stored procedures

JavaScript

yes

WarpScript

Triggers

JavaScript

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

yes

none

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

none

yes

Implicit feature of the cloud service

yes

selectable replication factor

based on HBase

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

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

ACID

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

with automatic compression on writes

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

Planned for future releases

Access rights can be defined down to the item level

yes

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

Specific characteristics

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more

Competitive advantages

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more

Typical application scenarios

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more

Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more

News

Mastering Memory Leak Detection in TDengine
31 May 2024

Seamless Data Integration from MQTT and InfluxDB to TDengine
22 May 2024

Solving Long Query Performance Bottlenecks
22 May 2024

What Is Predictive Maintenance?
17 May 2024

Can Typical Time-Series Databases Replace Data Historians?
8 May 2024

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.