DBMS > Alibaba Cloud MaxCompute vs. Google Cloud Bigtable vs. JanusGraph vs. RocksDB vs. Tibero

System Properties Comparison Alibaba Cloud MaxCompute vs. Google Cloud Bigtable vs. JanusGraph vs. RocksDB vs. Tibero

Editorial information provided by DB-Engines

Name

Description

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Relational DBMS

a graph-processing framework is available with the graphs being stored in tables

Key-value store
Wide column store

Graph DBMS

Key-value store

Relational DBMS

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

cloud.google.com/bigtable

janusgraph.org

rocksdb.org

us.tmaxsoft.com/products/tibero

Technical documentation

www.alibabacloud.com/help/en/maxcompute

cloud.google.com/bigtable/docs

docs.janusgraph.org

github.com/facebook/rocksdb/wiki

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Alibaba

Google

Linux Foundation; originally developed as Titan by Aurelius

Facebook, Inc.

TmaxSoft

Initial release

2016

2015

2017

2013

2003

Current release

0.6.3, February 2023

9.2.1, May 2024

6, April 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD

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

Java

C++

C and Assembler

Server operating systems

hosted

Linux
OS X
Unix
Windows

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

C++ API
Java API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

Java

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

Clojure
Java
Python

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

in Java

yes

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

Atomic single-row operations

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

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

yes

planned for next version

User concepts

Access control

Access rights for users and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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