DBMS > Google Cloud Bigtable vs. IBM Db2 Event Store vs. Microsoft Azure SQL Database vs. Riak KV vs. SAP Advantage Database Server

System Properties Comparison Google Cloud Bigtable vs. IBM Db2 Event Store vs. Microsoft Azure SQL Database vs. Riak KV vs. SAP Advantage Database Server

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.

Distributed Event Store optimized for Internet of Things use cases

Database as a Service offering with high compatibility to Microsoft SQL Server

Distributed, fault tolerant key-value store

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

Primary database model

Key-value store
Wide column store

Event Store
Time Series DBMS

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

cloud.google.com/bigtable

www.ibm.com/products/db2-event-store

azure.microsoft.com/en-us/products/azure-sql/database

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

Technical documentation

cloud.google.com/bigtable/docs

www.ibm.com/docs/en/db2-event-store

docs.microsoft.com/en-us/azure/azure-sql

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Google

IBM

Microsoft

OpenSource, formerly Basho Technologies

Sybase, SAP

Initial release

2015

2017

2010

2009

1993

Current release

2.0

V12

3.2.0, December 2022

License

Commercial or Open Source

commercial

free developer edition available

commercial

Open Source

Apache version 2, commercial enterprise edition

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

C and C++

C++

Erlang

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

hosted

Linux
OS X

Linux
Windows

Data scheme

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

restricted

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

APIs and other access methods

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

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

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

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

Transact SQL

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Active-active shard replication

yes, with always 3 replicas available

selectable replication factor

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)

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

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

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared 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)

fine grained access rights according to SQL-standard

yes, using Riak Security

fine grained access rights according to SQL-standard

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