DBMS > 4D vs. Apache Kylin vs. Datastax Enterprise vs. Google Cloud Datastore

System Properties Comparison 4D vs. Apache Kylin vs. Datastax Enterprise vs. Google Cloud Datastore

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

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.

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Primary database model

Relational DBMS

Wide column store

Document 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	2.37
Rank	#110	Overall
	#54	Relational DBMS

Score	1.14
Rank	#171	Overall
	#77	Relational DBMS

Score	4.82
Rank	#65	Overall
	#4	Wide column stores

Score	4.13
Rank	#71	Overall
	#12	Document stores

Website

www.4d.com

kylin.apache.org

www.datastax.com/products/datastax-enterprise

cloud.google.com/datastore

Technical documentation

developer.4d.com

kylin.apache.org/docs

docs.datastax.com

cloud.google.com/datastore/docs

Developer

4D, Inc

Apache Software Foundation, originally contributed from eBay Inc

DataStax

Google

Initial release

1984

2015

2011

2008

Current release

v20, April 2023

3.1.0, July 2020

6.8, April 2020

License

Commercial or Open Source

commercial

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.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

Implementation language

Java

Server operating systems

OS X
Windows

Linux

Linux
OS X

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, details here

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

yes

close to SQL 92

ANSI SQL for queries (using Apache Calcite)

SQL-like DML and DDL statements (CQL); Spark SQL

SQL-like query language (GQL)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC
RESTful HTTP API

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

Supported programming languages

4D proprietary IDE
PHP

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

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

Server-side scripts

Stored procedures

yes

using Google App Engine

Triggers

yes

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

Multi-source replication using Paxos

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

Users and groups

Access rights for users can be defined per object

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

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more

Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
» more

Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
» more

Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more

Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more

Licensing and pricing models

Annual subscription
» more

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

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

Overhauling Apache Kylin for the cloud
18 November 2021, InfoWorld

Migrating from ClickHouse to Apache Doris: Boosting OLAP Performance
9 October 2023, hackernoon.com

eBay’s Kylin Becomes a Top-Level Apache Open Source Project
9 December 2015, eBay Inc.

Distributed OLAPer Kyligence accelerates core engine, adds real-time data support
10 August 2021, Blocks & Files

How Kyligence Cloud uses Amazon EMR Serverless to simplify OLAP
9 November 2022, AWS Blog

provided by Google News

DataStax Enterprise 4.0 Gives in-Memory Option to Cassandra
31 May 2024, Data Center Knowledge

DataStax previews new Hyper Converged Data Platform for enterprise AI
15 May 2024, VentureBeat

DataStax to launch AI-integrated data platforms HCDP & DSE 6.9
16 May 2024, IT Brief Asia

DataStax Launches New Hyper-Converged Data Platform Giving Enterprises the Complete Modern Data Center Suite Needed for AI in Production
15 May 2024, Business Wire

DataStax acquires the startup behind low-code AI builder Langflow
4 April 2024, TechCrunch

provided by Google News

Google Cloud vs AWS: Which Cloud Computing Platform is Better?
11 September 2024, Cloudwards

Google Gets Rid of Fees To Transfer Data Out of Cloud Platform
12 January 2024, Spiceworks News and Insights

Best cloud storage of 2024
13 September 2024, TechRadar

Google App Engine
26 April 2024, TechTarget

17 Top Cloud Storage Companies to Know
9 April 2024, Built In

provided by Google News

Share this page