DBMS > Datastax Enterprise vs. GBase vs. Google Cloud Bigtable

System Properties Comparison Datastax Enterprise vs. GBase vs. Google Cloud Bigtable

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native 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.

Primary database model

Wide column store

Relational DBMS

Key-value store
Wide column store

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	3.94
Rank	#67	Overall
	#4	Wide column stores

Score	1.49
Rank	#142	Overall
	#64	Relational DBMS

Score	2.67
Rank	#93	Overall
	#15	Key-value stores
	#6	Wide column stores

Website

www.datastax.com/products/datastax-enterprise

www.gbase.cn

cloud.google.com/bigtable

Technical documentation

docs.datastax.com

cloud.google.com/bigtable/docs

Developer

DataStax

General Data Technology Co., Ltd.

Google

Initial release

2011

2004

2015

Current release

6.8, April 2020

GBase 8a, GBase 8s, GBase 8c

License

Commercial or 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

Java

C, Java, Python

Server operating systems

Linux
OS X

Linux

hosted

Data scheme

schema-free

yes

schema-free

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 DML and DDL statements (CQL); Spark SQL

Standard with numerous extensions

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

ADO.NET
C API
JDBC
ODBC

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

Supported programming languages

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

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

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware, advanced replication for edge computing

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Atomic single-row operations

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.

yes

User concepts

Access control

Access rights for users can be defined per object

yes

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

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

IBM to acquire DataStax, helping clients bring the power of unstructured data to enterprise AI applications
25 February 2025, IBM

Big Blue To Acquire Datastax in Enterprise AI Play
28 February 2025, Redmond Channel Partner

IBM to Acquire DataStax, Deepening watsonx Capabilities and Addressing Generative AI Data Needs for the Enterprise
25 February 2025, PR Newswire

IBM To Buy DataStax, Expand Watsonx AI Portfolio’s Data Management Capabilities
25 February 2025, CRN Magazine

IBM to Acquire DataStax to Power Generative AI, Tapping into 93% of Enterprise Data
26 February 2025, eWEEK

provided by Google News

What’s next for Google Cloud databases? AI inside SQL and more
9 April 2025, VentureBeat

Google introduces Bigtable SQL access and Spanner's new AI-ready features
1 August 2024, ZDNet

Google Cloud adds graph processing to Spanner, SQL support to Bigtable
1 August 2024, InfoWorld

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

Google Introduces Zero-ETL Approach to Analytics on Bigtable Data Using BigQuery
11 August 2022, infoq.com

provided by Google News

Share this page