DBMS > Google Cloud Bigtable vs. RavenDB vs. SAP IQ vs. Snowflake vs. TDSQL for MySQL

System Properties Comparison Google Cloud Bigtable vs. RavenDB vs. SAP IQ vs. Snowflake vs. TDSQL for MySQL

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.

Open Source Operational and Transactional Enterprise NoSQL Document Database

Columnar RDBMS optimized for Big Data analytics

Cloud-based data warehousing service for structured and semi-structured data

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Key-value store
Wide column store

Document store

Relational DBMS

column-oriented

Relational DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
Spatial 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	2.84
Rank	#101	Overall
	#18	Document stores

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Website

cloud.google.com/bigtable

ravendb.net

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.snowflake.com

www.tencentcloud.com/products/dcdb

Technical documentation

cloud.google.com/bigtable/docs

ravendb.net/docs

help.sap.com/docs/SAP_IQ

docs.snowflake.net/manuals/index.html

www.tencentcloud.com/document/product/1042

Developer

Google

Hibernating Rhinos

SAP, formerly Sybase

Snowflake Computing Inc.

Tencent

Initial release

2015

2010

1994

2014

2013

Current release

5.4, July 2022

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

Open Source

AGPL version 3, commercial license available

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
macOS
Raspberry Pi
Windows

AIX
HP-UX
Linux
Solaris
Windows

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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 (RQL)

yes

APIs and other access methods

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

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

ADO.NET
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

JDBC
ODBC

Supported programming languages

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

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

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

yes

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

SAP/Sybase Replication Server

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

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, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

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

Authorization levels configured per client per database

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

Users with fine-grained authorization concept

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.