DBMS > Apache Doris vs. Google BigQuery vs. InfluxDB vs. Memcached vs. Sadas Engine

System Properties Comparison Apache Doris vs. Google BigQuery vs. InfluxDB vs. Memcached vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

Large scale data warehouse service with append-only tables

DBMS for storing time series, events and metrics

In-memory key-value store, originally intended for caching

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Secondary database models

Spatial DBMS

with GEO package

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

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

cloud.google.com/bigquery

www.influxdata.com/products/influxdb-overview

www.memcached.org

www.sadasengine.com

Technical documentation

github.com/apache/doris/wiki

cloud.google.com/bigquery/docs

docs.influxdata.com/influxdb

github.com/memcached/memcached/wiki

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Apache Software Foundation, originally contributed from Baidu

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

SADAS s.r.l.

Initial release

2017

2010

2013

2003

2006

Current release

1.2.2, February 2023

2.7.6, April 2024

1.6.27, May 2024

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

BSD license

commercial

free trial version available

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
OS X

through Homebrew

FreeBSD
Linux
OS X
Unix
Windows

AIX
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

JDBC
MySQL client

RESTful HTTP/JSON API

HTTP API
JSON over UDP

Proprietary protocol

JDBC
ODBC
Proprietary protocol

Supported programming languages

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

in enterprise version only

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

in enterprise version only

none

Repcached, a Memcached patch, provides this functionallity

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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.

yes

Depending on used storage engine

yes

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

simple rights management via user accounts

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights for users, groups and roles according to SQL-standard

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