DBMS > Altibase vs. Apache IoTDB vs. Google Cloud Bigtable vs. InterSystems IRIS vs. Snowflake

System Properties Comparison Altibase vs. Apache IoTDB vs. Google Cloud Bigtable vs. InterSystems IRIS vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

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

Primary database model

Relational DBMS

Time Series DBMS

Key-value store
Wide column store

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	4.05
Rank	#83	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

altibase.com

iotdb.apache.org

cloud.google.com/bigtable

www.intersystems.com/products/intersystems-iris

www.snowflake.com

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

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

cloud.google.com/bigtable/docs

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

docs.snowflake.net/manuals/index.html

Developer

Altibase

Apache Software Foundation

Google

InterSystems

Snowflake Computing Inc.

Initial release

1999

2018

2015

2018

2014

Current release

v7.3, 2023, August 2023

1.1.0, April 2023

2023.3, June 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

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

C++

Java

Server operating systems

AIX
HP-UX
Linux

All OS with a Java VM (>= 1.8)

hosted

AIX
Linux
macOS
Ubuntu
Windows

hosted

Data scheme

yes

schema-free

depending on used data model

yes

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

Typing

predefined data types such as float or date

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

SQL

Support of SQL

ANSI SQL-92

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
Native API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

C
C++
Java

C
C#
C++
Go
Java
Python
Scala

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

.Net
C++
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

user defined functions

Triggers

yes

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)

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Internal replication in Colossus, and regional replication between two clusters in different zones

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

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

fine grained access rights according to SQL-standard

yes

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

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

More information provided by the system vendor

Specific characteristics

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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