DBMS > Microsoft Azure Cosmos DB vs. ObjectBox vs. Tarantool vs. VictoriaMetrics

System Properties Comparison Microsoft Azure Cosmos DB vs. ObjectBox vs. Tarantool vs. VictoriaMetrics

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Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Object oriented DBMS
Vector DBMS

Document store
Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

Spatial DBMS

with Tarantool/GIS extension

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

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

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS
	#7	Vector DBMS

Score	1.67
Rank	#143	Overall
	#25	Document stores
	#25	Key-value stores
	#65	Relational DBMS

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

azure.microsoft.com/services/cosmos-db

github.com/objectbox
objectbox.io

www.tarantool.io

victoriametrics.com

Technical documentation

learn.microsoft.com/azure/cosmos-db

docs.objectbox.io

www.tarantool.io/en/doc

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Microsoft

ObjectBox Limited

VictoriaMetrics

Initial release

2014

2017

2008

2018

Current release

4.0 (May 2024)

2.10.0, May 2022

v1.91, May 2023

License

Commercial or Open Source

commercial

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

Open Source

Apache Version 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 and C++

Server operating systems

hosted

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

BSD
Linux
macOS

FreeBSD
Linux
macOS
OpenBSD

Data scheme

schema-free

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

JSON types

yes, plus "flex" map-like types

string, double, decimal, uuid, integer, blob, boolean, datetime

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

yes

SQL

Support of SQL

SQL-like query language

Full-featured ANSI SQL support

APIs and other access methods

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

Proprietary native API

Open binary protocol

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

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

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

JavaScript

Lua, C and SQL stored procedures

Triggers

JavaScript

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Data sync between devices allowing occasional connected databases to work completely offline

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

Synchronous replication

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

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

yes, write ahead logging

yes

In-memory capabilities

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

yes, full featured in-memory storage engine with persistence

User concepts

Access control

Access rights can be defined down to the item level

yes

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

More information provided by the system vendor

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