DBMS > CrateDB vs. Datastax Enterprise vs. Heroic vs. Machbase Neo

System Properties Comparison CrateDB vs. Datastax Enterprise vs. Heroic vs. Machbase Neo

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

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.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

TimeSeries DBMS for AIoT and BigData

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Wide column store

Time Series DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	0.64
Rank	#225	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#12	Vector DBMS

Score	4.91
Rank	#63	Overall
	#4	Wide column stores

Score	0.02
Rank	#368	Overall
	#38	Time Series DBMS

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Website

cratedb.com

www.datastax.com/products/datastax-enterprise

github.com/spotify/heroic

machbase.com

Technical documentation

cratedb.com/docs

docs.datastax.com

spotify.github.io/heroic

machbase.com/dbms

Developer

Crate

DataStax

Spotify

Machbase

Initial release

2013

2011

2014

2013

Current release

5.8.1, August 2024

6.8, April 2020

V8.0, August 2023

License

Commercial or Open Source

Open Source

commercial

Open Source

Apache 2.0

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

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux
OS X

Linux
macOS
Windows

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

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

via Elasticsearch

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

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

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

HQL (Heroic Query Language, a JSON-based language)
HTTP API

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

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

user defined functions (Javascript)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

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

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

Atomicity and isolation are supported for single 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

volatile and lookup table

User concepts

Access control

rights management via user accounts

Access rights for users can be defined per object

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

Recent citations in the news

CrateDB, a name that we will hear more in the future
24 October 2024, AWS Blog

Crate.io Introduces CrateDB 2.0 Enterprise and Open Source Editions
16 May 2017, Business Wire

CrateDB Announces New Executive Leadership Appointments
29 August 2023, PR Newswire

CrateDB: The IoT and machine data-focused database
14 December 2016, Network World

Crate.io Brings Power of Industrial SQL Time Series to Azure IoT Hub to Reduce IoT Systems Cost and Complexity
24 September 2018, Business Wire

provided by Google News

DataStax Announces Vector Search for DataStax Enterprise: Bringing the Power of Generative AI to Any Cloud, Hybrid, and On-premises Environments
8 August 2023, Business Wire

US Bank is using DataStax Enterprise to overcome legacy and become customer focused
23 May 2019, diginomica

DataStax review: Cassandra made faster and easier
20 August 2018, InfoWorld

DataStax Luna: Subscription-Based Support for Open-Source Apache Cassandra
20 September 2021, ibm.com

NetApp stacks DataStax onto its Astra Kubernetes storage
20 May 2021, Blocks & Files

provided by Google News

How Code Wizards load tested Heroic Labs’ Nakama to two million concurrent players with AWS
1 October 2024, AWS Blog

provided by Google News

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