DBMS > Apache Impala vs. Apache IoTDB vs. Memcached vs. Microsoft Azure Cosmos DB vs. Snowflake

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Memcached vs. Microsoft Azure Cosmos DB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

In-memory key-value store, originally intended for caching

Globally distributed, horizontally scalable, multi-model database service

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Time Series DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Document store

Spatial DBMS

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	16.84
Rank	#32	Overall
	#4	Key-value stores

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

impala.apache.org

iotdb.apache.org

www.memcached.org

azure.microsoft.com/services/cosmos-db

www.snowflake.com

Technical documentation

impala.apache.org/impala-docs.html

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

github.com/memcached/memcached/wiki

learn.microsoft.com/azure/cosmos-db

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

Snowflake Computing Inc.

Initial release

2013

2018

2003

2014

Current release

4.1.0, June 2022

1.1.0, April 2023

1.6.29, June 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

BSD license

commercial

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++

Java

Server operating systems

Linux

All OS with a Java VM (>= 1.8)

FreeBSD
Linux
OS X
Unix
Windows

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

JDBC
Native API

Proprietary protocol

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

CLI Client
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

JavaScript

user defined functions

Triggers

yes

JavaScript

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

none

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

none

Repcached, a Memcached patch, provides this functionallity

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Integration with Hadoop and Spark

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Strong Consistency with Raft

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights can be defined down to the item level

Users with fine-grained authorization concept, user roles and pluggable authentication

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