DBMS > Axibase vs. Google BigQuery vs. Kyligence Enterprise vs. RethinkDB vs. Rockset

System Properties Comparison Axibase vs. Google BigQuery vs. Kyligence Enterprise vs. RethinkDB vs. Rockset

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

A distributed analytics engine for big data, built on top of Apache Kylin

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

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

Primary database model

Time Series DBMS

Relational DBMS

Document store

Secondary database models

Spatial DBMS

Relational DBMS
Search engine

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

Score	0.32
Rank	#288	Overall
	#25	Time Series DBMS

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	0.39
Rank	#276	Overall
	#125	Relational DBMS

Score	2.84
Rank	#106	Overall
	#19	Document stores

Score	0.84
Rank	#209	Overall
	#35	Document stores

Website

axibase.com/docs/atsd/finance

cloud.google.com/bigquery

kyligence.io/kyligence-enterprise

rethinkdb.com

rockset.com

Technical documentation

cloud.google.com/bigquery/docs

rethinkdb.com/docs

docs.rockset.com

Developer

Axibase Corporation

Google

Kyligence, Inc.

The Linux Foundation

since July 2017

Rockset

Initial release

2013

2010

2016

2009

2019

Current release

15585

2.4.1, August 2020

License

Commercial or Open Source

commercial

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

commercial

Open Source

Apache Version 2

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

Linux

Linux
OS X
Windows

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

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

yes

string, binary, float, bool, date, geometry

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

ANSI SQL for queries (using Apache Calcite)

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

HTTP REST

Supported programming languages

Go
Java
PHP
Python
R
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

range based

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

users and table-level permissions

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

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