DBMS > Apache Druid vs. Datastax Enterprise vs. Hyprcubd vs. Ingres vs. Newts

System Properties Comparison Apache Druid vs. Datastax Enterprise vs. Hyprcubd vs. Ingres vs. Newts

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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.

Serverless Time Series DBMS

Well established RDBMS

Time Series DBMS based on Cassandra

Primary database model

Relational DBMS
Time Series DBMS

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	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	4.82
Rank	#65	Overall
	#4	Wide column stores

Score	3.63
Rank	#79	Overall
	#43	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

druid.apache.org

www.datastax.com/products/datastax-enterprise

hyprcubd.com (offline)

www.actian.com/databases/ingres

opennms.github.io/newts

Technical documentation

druid.apache.org/docs/latest/design

docs.datastax.com

docs.actian.com/ingres

github.com/OpenNMS/newts/wiki

Developer

Apache Software Foundation and contributors

DataStax

Hyprcubd, Inc.

Actian Corporation

OpenNMS Group

Initial release

2012

2011

1974

originally developed at University Berkely in early 1970s

2014

Current release

30.0.0, June 2024

6.8, April 2020

12.0, July 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache 2.0

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

Linux
OS X
Unix

Linux
OS X

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

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

SQL-like query language

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

gRPC (https)

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

HTTP REST
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

no "single point of failure"

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

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

Ingres Replicator

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Eventual Consistency

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users can be defined per object

token access

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Licensing and pricing models

Annual subscription
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