DBMS > Couchbase vs. CrateDB vs. eXtremeDB vs. Hypertable vs. Microsoft Access

System Properties Comparison Couchbase vs. CrateDB vs. eXtremeDB vs. Hypertable vs. Microsoft Access

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Distributed Database based on Lucene

Natively in-memory DBMS with options for persistency, high-availability and clustering

An open source BigTable implementation based on distributed file systems such as Hadoop

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Primary database model

Document store

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS
Time Series DBMS

Wide column store

Relational DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.73
Rank	#224	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Website

www.couchbase.com

cratedb.com

www.mcobject.com

www.microsoft.com/en-us/microsoft-365/access

Technical documentation

docs.couchbase.com

cratedb.com/docs

www.mcobject.com/docs/extremedb.htm

developer.microsoft.com/en-us/access

Developer

Couchbase, Inc.

Crate

McObject

Hypertable Inc.

Microsoft

Initial release

2011

2013

2001

2009

1992

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

8.2, 2021

0.9.8.11, March 2016

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

commercial

Open Source

GNU version 3. Commercial license available

commercial

Bundled with Microsoft Office

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.

CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.

Implementation language

C, C++, Go and Erlang

Java

C and C++

C++

Server operating systems

Linux
OS X
Windows

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
OS X
Windows

an inofficial Windows port is available

Windows

Not a real database server, but making use of DLLs

Data scheme

schema-free

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

yes

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.

support of XML interfaces available

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

with the option: eXtremeSQL

yes

but not compliant to any SQL standard

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

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

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

C++ API
Thrift

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.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

.Net
C
C#
C++
Java
Lua
Python
Scala

C++
Java
Perl
PHP
Python
Ruby

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

user defined functions (Javascript)

yes

since Access 2010 using the ACE-engine

Triggers

yes

via the TAP protocol

yes

by defining events

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

horizontal partitioning / sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Configurable replication on table/partition-level

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

selectable replication factor on file system level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

In-memory capabilities

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

yes

Ephemeral buckets

yes

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

rights management via user accounts

a simple user-level security was built in till version Access 2003

More information provided by the system vendor

Specific characteristics

The enterprise database for time series, documents, and vectors. Distributed - Native...
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eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantages

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
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eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
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IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Across all continents, CrateDB is used by companies of all sizes to meet the most...
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Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
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With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

See CrateDB pricing >
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For server use cases, there is a simple per-server license irrespective of the number...
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