DBMS > Axibase vs. Google Cloud Spanner vs. InterSystems IRIS vs. Snowflake vs. TerarkDB

System Properties Comparison Axibase vs. Google Cloud Spanner vs. InterSystems IRIS vs. Snowflake vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

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

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Time Series DBMS

Relational DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Key-value store

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	3.54
Rank	#84	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

axibase.com/docs/atsd/finance

cloud.google.com/spanner

www.intersystems.com/products/intersystems-iris

www.snowflake.com

github.com/bytedance/terarkdb

Technical documentation

cloud.google.com/spanner/docs

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

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Axibase Corporation

Google

InterSystems

Snowflake Computing Inc.

ByteDance, originally Terark

Initial release

2013

2017

2018

2014

2016

Current release

15585

2023.3, June 2023

License

Commercial or Open Source

commercial

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

commercial

restricted open source version available

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++

Server operating systems

Linux

hosted

AIX
Linux
macOS
Ubuntu
Windows

hosted

Data scheme

yes

depending on used data model

yes

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

schema-free

Typing

predefined data types such as float or date

yes

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

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

SQL-like query language

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

C++ API
Java API

Supported programming languages

Go
Java
PHP
Python
R
Ruby

Go
Java
JavaScript (Node.js)
Python

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

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication with 3 replicas for regional instances.

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

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 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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