DBMS > Apache Doris vs. Apache Druid vs. Google BigQuery vs. SAP Adaptive Server vs. TDengine

System Properties Comparison Apache Doris vs. Apache Druid vs. Google BigQuery vs. SAP Adaptive Server vs. TDengine

Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Large scale data warehouse service with append-only tables

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Time Series DBMS and big data platform

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

Relational DBMS

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	36.31
Rank	#25	Overall
	#17	Relational DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

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

druid.apache.org

cloud.google.com/bigquery

www.sap.com/products/technology-platform/sybase-ase.html

github.com/taosdata/TDengine
tdengine.com

Technical documentation

github.com/apache/doris/wiki

druid.apache.org/docs/latest/design

cloud.google.com/bigquery/docs

help.sap.com/docs/SAP_ASE

docs.tdengine.com

Developer

Apache Software Foundation, originally contributed from Baidu

Apache Software Foundation and contributors

Google

SAP, Sybase

TDEngine, previously Taos Data

Initial release

2017

2012

2010

1987

2019

Current release

1.2.2, February 2023

29.0.1, April 2024

16.0

3.0, August 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache license v2

commercial

Open Source

AGPL V3, also commercial editions 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 and C++

Server operating systems

Linux

Linux
OS X
Unix

hosted

AIX
HP-UX
Linux
Solaris
Unix
Windows

Linux
Windows

Data scheme

yes

schema-less columns are supported

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL for querying

yes

Standard SQL with extensions for time-series applications

APIs and other access methods

JDBC
MySQL client

JDBC
RESTful HTTP/JSON API

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
RESTful HTTP API

Supported programming languages

Java

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Cobol
Java
Java
Perl
PHP
Python

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Java and Transact-SQL

Triggers

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

manual/auto, time-based

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, via HDFS, S3 or other storage engines

Multi-source replication
Source-replica replication

yes

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

ACID

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

fine grained access rights according to SQL-standard

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Market metrics

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Licensing and pricing models

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