DBMS > ArcadeDB vs. Datastax Enterprise vs. SpaceTime

System Properties Comparison ArcadeDB vs. Datastax Enterprise vs. SpaceTime

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Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

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.

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Wide column store

Spatial 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	0.09
Rank	#355	Overall
	#48	Document stores
	#37	Graph DBMS
	#52	Key-value stores
	#34	Time Series DBMS

Score	6.31
Rank	#57	Overall
	#4	Wide column stores

Score	0.00
Rank	#396	Overall
	#8	Spatial DBMS

Website

arcadedb.com

www.datastax.com/products/datastax-enterprise

www.mireo.com/spacetime

Technical documentation

docs.arcadedb.com

docs.datastax.com

Developer

Arcade Data

DataStax

Mireo

Initial release

2021

2011

2020

Current release

September 2021

6.8, April 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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++

Server operating systems

All OS with a Java VM

Linux
OS X

Linux

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-like query language, no joins

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

A subset of ANSI SQL is implemented

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

RESTful HTTP API

Supported programming languages

Java

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

C#
C++
Python

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

Real-time block device replication (DRBD)

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

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

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

User concepts

Access control

Access rights for users can be defined per object

yes

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...
» 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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