DBMS > Apache Impala vs. InfluxDB vs. Microsoft Azure Cosmos DB vs. ObjectBox

System Properties Comparison Apache Impala vs. InfluxDB vs. Microsoft Azure Cosmos DB vs. ObjectBox

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

DBMS for storing time series, events and metrics

Globally distributed, horizontally scalable, multi-model database service

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Object oriented DBMS

Secondary database models

with GEO package

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	26.56
Rank	#28	Overall
	#1	Time Series DBMS

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.22
Rank	#172	Overall
	#5	Object oriented DBMS

Website

impala.apache.org

www.influxdata.com/products/influxdb-overview

azure.microsoft.com/services/cosmos-db

objectbox.io

Technical documentation

impala.apache.org/impala-docs.html

docs.influxdata.com/influxdb

learn.microsoft.com/azure/cosmos-db

docs.objectbox.io

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Microsoft

ObjectBox Limited

Initial release

2013

2014

2017

Current release

4.1.0, June 2022

2.7.5, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT-License; commercial enterprise version available

commercial

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

Server operating systems

Linux

Linux
OS X

through Homebrew

hosted

Android
iOS
Linux
macOS
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC
ODBC

HTTP API
JSON over UDP

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

Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

JavaScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

in enterprise version only

yes

Implicit feature of the cloud service

online/offline synchronization between client and server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate 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

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

Depending on used storage engine

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

simple rights management via user accounts

Access rights can be defined down to the item level

yes

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

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Licensing and pricing models

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.