DBMS > Alibaba Cloud AnalyticDB for MySQL vs. Google BigQuery vs. GreptimeDB vs. Quasardb vs. TimesTen

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. Google BigQuery vs. GreptimeDB vs. Quasardb vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

A real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.

Large scale data warehouse service with append-only tables

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Distributed, high-performance timeseries database

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store

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

Score	0.85
Rank	#207	Overall
	#96	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.alibabacloud.com/product/analyticdb-for-mysql

cloud.google.com/bigquery

greptime.com

quasar.ai

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

www.alibabacloud.com/help/doc-detail/93776.htm

cloud.google.com/bigquery/docs

docs.greptime.com

doc.quasar.ai/master

docs.oracle.com/database/timesten-18.1

Developer

Alibaba

Google

Greptime Inc.

quasardb

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2010

2022

2009

1998

Current release

3.14.1, January 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

Rust

C++

Server operating systems

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

BSD
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free, schema definition possible

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

gRPC
HTTP API
JDBC

HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C#
Java
PHP
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Erlang
Go
Java
JavaScript

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Python

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication with selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

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

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

A real-time data warehousing service that can process PB data with high concurrency...
» more

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

TPC Benchmark: The world leading result in TPC-DS benchmark . TPC-H benchmark for...
» more

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

Available regions: America US Virginia US Silicon Valley Asia China Hong Kong India...
» more

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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