DBMS > Google BigQuery vs. RethinkDB vs. Splunk vs. STSdb vs. Warp 10

System Properties Comparison Google BigQuery vs. RethinkDB vs. Splunk vs. STSdb vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

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

Analytics Platform for Big Data

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Secondary database models

Spatial DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

cloud.google.com/bigquery

rethinkdb.com

www.splunk.com

github.com/STSSoft/STSdb4

www.warp10.io

Technical documentation

cloud.google.com/bigquery/docs

rethinkdb.com/docs

docs.splunk.com/Documentation/Splunk

www.warp10.io/content/02_Getting_started

Developer

Google

The Linux Foundation

since July 2017

Splunk Inc.

STS Soft SC

SenX

Initial release

2010

2009

2003

2011

2015

Current release

2.4.1, August 2020

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

Limited free edition and free developer edition available

Open Source

GPLv2, commercial license available

Open Source

Apache License 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

C++

Java

Server operating systems

hosted

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

yes

primitive types and user defined types (classes)

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

yes

Splunk Search Processing Language for search commands

APIs and other access methods

RESTful HTTP/JSON API

HTTP REST

.NET Client API

HTTP API
Jupyter
WebSocket

Supported programming languages

.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

C#
Java
JavaScript
PHP
Python
Ruby

C#
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

WarpScript

Triggers

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

range based

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

none

selectable replication factor

based on HBase

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

based on HBase

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

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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.

yes

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 roles

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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