DBMS > Google Cloud Bigtable vs. OrigoDB vs. SAP SQL Anywhere vs. Transwarp KunDB

System Properties Comparison Google Cloud Bigtable vs. OrigoDB vs. SAP SQL Anywhere vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

Description

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 fully ACID in-memory object graph database

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Key-value store
Wide column store

Document store
Object oriented DBMS

Relational DBMS

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

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

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Website

cloud.google.com/bigtable

origodb.com

www.sap.com/products/technology-platform/sql-anywhere.html

www.transwarp.cn/en/product/kundb

Technical documentation

cloud.google.com/bigtable/docs

origodb.com/docs

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Google

Robert Friberg et al

SAP

formerly Sybase

Transwarp

Initial release

2015

2009

under the name LiveDB

1992

Current release

17, July 2015

License

Commercial or Open Source

commercial

Open Source

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

Server operating systems

hosted

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

User defined using .NET types and collections

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.

can be achieved using .NET

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

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

.NET Client API
HTTP API
LINQ

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

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

.Net

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

yes, in C/C++, Java, .Net or Perl

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Foreign keys

Referential integrity

depending on model

yes

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Role based authorization

fine grained access rights according to SQL-standard

yes

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