DBMS > Apache Drill vs. Datastax Enterprise vs. DolphinDB vs. Graph Engine vs. Machbase Neo

System Properties Comparison Apache Drill vs. Datastax Enterprise vs. DolphinDB vs. Graph Engine vs. Machbase Neo

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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.

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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

TimeSeries DBMS for AIoT and BigData

Primary database model

Document store
Relational DBMS

Wide column store

Time Series DBMS

Graph DBMS
Key-value store

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Relational DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Website

drill.apache.org

www.datastax.com/products/datastax-enterprise

www.dolphindb.com

www.graphengine.io

machbase.com

Technical documentation

drill.apache.org/docs

docs.datastax.com

docs.dolphindb.cn/en/help200/index.html

www.graphengine.io/docs/manual

machbase.com/dbms

Developer

Apache Software Foundation

DataStax

DolphinDB, Inc

Microsoft

Machbase

Initial release

2012

2011

2018

2010

2013

Current release

1.20.3, January 2023

6.8, April 2020

v2.00.4, January 2022

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free community version available

Open Source

MIT License

commercial

free test version available

Cloud-based only

Only available as a cloud service

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

C++

.NET and C

Server operating systems

Linux
OS X
Windows

Linux
OS X

Linux
Windows

.NET

Linux
macOS
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

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

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

RESTful HTTP API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

C++

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

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C#
C++
F#
Visual Basic

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomicity and isolation are supported for single operations

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

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

In-memory capabilities

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

Depending on the underlying data source

yes

volatile and lookup table

User concepts

Access control

Depending on the underlying data source

Access rights for users can be defined per object

Administrators, Users, Groups

simple password-based access control

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

Recent citations in the news

Analyse Kafka messages with SQL queries using Apache Drill
23 September 2019, Towards Data Science

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Using Apache Iceberg for Developing Modern Data Tables
3 October 2023, Open Source For You

Apache Drill improves big data SQL query engine
31 August 2021, TechTarget

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

provided by Google News

DataStax and LlamaIndex Partner to Make Building RAG Applications Easier than Ever for GenAI Developers
20 February 2024, Business Wire

DataStax Introduces Enhanced RAG Capabilities Through Astra DB and NVIDIA Tech
19 March 2024, Datanami

DataStax Rolls Out Vector Search for Astra DB to Support Gen AI
19 July 2023, EnterpriseAI

DataStax adds vector search to boost support for generative AI workloads
18 July 2023, SiliconANGLE News

DataStax goes vector searching with Astra DB – Blocks and Files
20 July 2023, Blocks and Files

provided by Google News

Trinity
2 June 2023, 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

How Google and Microsoft taught search to "understand" the Web
6 June 2012, Ars Technica

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

provided by Google News

“Luxembourg is a perfect target area”: Korean accelerator exec
27 October 2022, Delano.lu

provided by Google News

Share this page