DBMS > Axibase vs. Drizzle vs. GreptimeDB vs. Microsoft Azure Cosmos DB

System Properties Comparison Axibase vs. Drizzle vs. GreptimeDB vs. Microsoft Azure Cosmos DB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

axibase.com/docs/atsd/finance

greptime.com

azure.microsoft.com/services/cosmos-db

Technical documentation

docs.greptime.com

learn.microsoft.com/azure/cosmos-db

Developer

Axibase Corporation

Drizzle project, originally started by Brian Aker

Greptime Inc.

Microsoft

Initial release

2013

2008

2022

2014

Current release

15585

7.2.4, September 2012

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

GNU GPL

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

Java

C++

Rust

Server operating systems

Linux

FreeBSD
Linux
OS X

Android
Docker
FreeBSD
Linux
macOS
Windows

hosted

Data scheme

yes

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

JSON types

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

yes

with proprietary extensions

yes

SQL-like query language

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC

gRPC
HTTP API
JDBC

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

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C
C++
Java
PHP

C++
Erlang
Go
Java
JavaScript

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

Server-side scripts

Stored procedures

yes

Python

JavaScript

Triggers

yes

hooks for callbacks inside the server can be used.

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Foreign keys

Referential integrity

yes

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

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Simple rights management via user accounts

Access rights can be defined down to the item level

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
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Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
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Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
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