DBMS > Axibase vs. Google BigQuery vs. Heroic vs. searchxml

System Properties Comparison Axibase vs. Google BigQuery vs. Heroic vs. searchxml

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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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

Native XML 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	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	0.01
Rank	#386	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

axibase.com/docs/atsd/finance

cloud.google.com/bigquery

github.com/spotify/heroic

www.searchxml.net/category/products

Technical documentation

cloud.google.com/bigquery/docs

spotify.github.io/heroic

www.searchxml.net/support/handouts

Developer

Axibase Corporation

Google

Spotify

informationpartners gmbh

Initial release

2013

2010

2014

2015

Current release

15585

1.0

License

Commercial or Open Source

commercial

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

commercial

Open Source

Apache 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

Java

C++

Server operating systems

Linux

hosted

Windows

Data scheme

yes

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

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

RESTful HTTP/JSON API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

Go
Java
PHP
Python
R
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

sychronisation to multiple collections

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
Immediate Consistency

Immediate 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

multiple readers, single writer

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)

Domain, group and role-based access control at the document level and for application services

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