DBMS > Google BigQuery vs. Heroic vs. Riak TS vs. searchxml vs. TinkerGraph

System Properties Comparison Google BigQuery vs. Heroic vs. Riak TS vs. searchxml vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

DBMS for structured and unstructured content wrapped with an application server

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Relational DBMS

Time Series DBMS

Native XML DBMS
Search engine

Graph DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

cloud.google.com/bigquery

github.com/spotify/heroic

www.searchxml.net/category/products

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

cloud.google.com/bigquery/docs

spotify.github.io/heroic

www.tiot.jp/riak-docs/riak/ts/latest

www.searchxml.net/support/handouts

Developer

Google

Spotify

Open Source, formerly Basho Technologies

informationpartners gmbh

Initial release

2010

2014

2015

2009

Current release

3.0.0, September 2022

1.0

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

commercial

Open Source

Apache 2.0

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

Erlang

C++

Java

Server operating systems

hosted

Linux
OS X

Windows

Data scheme

yes

schema-free

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

via Elasticsearch

restricted

yes

SQL

Support of SQL

yes

yes, limited

APIs and other access methods

RESTful HTTP/JSON API

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

HTTP API
Native Erlang Interface

RESTful HTTP API
WebDAV
XQuery
XSLT

TinkerPop 3

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C++

most other programming languages supported via APIs

Groovy
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Erlang

yes

on the application server

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

sychronisation to multiple collections

none

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

Eventual Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

links between datasets can be stored

yes

Relationships in graphs

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

optional

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 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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