DBMS > Google Cloud Bigtable vs. Graph Engine vs. openGemini vs. SAP Advantage Database Server

System Properties Comparison Google Cloud Bigtable vs. Graph Engine vs. openGemini vs. SAP Advantage Database Server

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Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Key-value store
Wide column store

Graph DBMS
Key-value store

Time Series 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	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.09
Rank	#361	Overall
	#37	Time Series DBMS

Website

cloud.google.com/bigtable

www.graphengine.io

www.opengemini.org
github.com/openGemini

www.sap.com/products/advantage-database-server.html

Technical documentation

cloud.google.com/bigtable/docs

www.graphengine.io/docs/manual

docs.opengemini.org/guide

Developer

Google

Microsoft

Huawei and openGemini community

Sybase, SAP

Initial release

2015

2010

2022

1993

Current release

1.1, July 2023

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache Version 2.0

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

.NET and C

Server operating systems

hosted

.NET

Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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

SQL-like query language

yes

APIs and other access methods

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

RESTful HTTP API

HTTP REST

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

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

C#
C++
F#
Visual Basic

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

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

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

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

yes

caching of (temporary) tables can be configured

User concepts

Access control

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

Administrators and common users accounts

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

provided by Google News

Trinity
30 October 2010, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

The graph analytics landscape 2019 - DataScienceCentral.com
27 February 2019, Data Science Central

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

provided by Google News

About HUAWEI Open Source
9 February 2022, Huawei

provided by Google News

SAP Announces Q3 2023 Results: Asia Pacific and Japan View
19 October 2023, SAP News

provided by Google News

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