DBMS > Axibase vs. Google BigQuery vs. Microsoft Azure AI Search vs. Rockset

System Properties Comparison Axibase vs. Google BigQuery vs. Microsoft Azure AI Search vs. Rockset

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Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

Search-as-a-service for web and mobile app development

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Secondary database models

Vector DBMS

Relational DBMS
Search engine

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

axibase.com/docs/atsd/finance

cloud.google.com/bigquery

azure.microsoft.com/en-us/services/search

rockset.com

Technical documentation

cloud.google.com/bigquery/docs

learn.microsoft.com/en-us/azure/search

docs.rockset.com

Developer

Axibase Corporation

Google

Microsoft

Rockset

Initial release

2013

2010

2015

2019

Current release

15585

License

Commercial or Open Source

commercial

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

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

Java

C++

Server operating systems

Linux

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

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

yes

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

yes

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

RESTful HTTP/JSON API

RESTful HTTP API

HTTP REST

Supported programming languages

Go
Java
PHP
Python
R
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
JavaScript
Python

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

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.

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

using Azure authentication

Access rights for users and organizations can be defined via Rockset console

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