DBMS > Couchbase vs. Hazelcast vs. Kyligence Enterprise vs. Microsoft Azure Synapse Analytics vs. OrigoDB

System Properties Comparison Couchbase vs. Hazelcast vs. Kyligence Enterprise vs. Microsoft Azure Synapse Analytics vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

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

A widely adopted in-memory data grid

A distributed analytics engine for big data, built on top of Apache Kylin

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

A fully ACID in-memory object graph database

Primary database model

Document store

Key-value store

Relational DBMS

Document store
Object oriented 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

Document store

JSON support with IMDG 3.12

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

www.couchbase.com

hazelcast.com

kyligence.io/kyligence-enterprise

azure.microsoft.com/services/synapse-analytics

origodb.com

Technical documentation

docs.couchbase.com

hazelcast.org/imdg/docs

docs.microsoft.com/azure/synapse-analytics

origodb.com/docs

Developer

Couchbase, Inc.

Hazelcast

Kyligence, Inc.

Microsoft

Robert Friberg et al

Initial release

2011

2008

2016

2009

under the name LiveDB

Current release

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

5.3.6, November 2023

License

Commercial or Open Source

Open Source

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

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

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.

Implementation language

C, C++, Go and Erlang

Java

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux

hosted

Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

yes

the object must implement a serialization strategy

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

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

SQL-like query language

ANSI SQL for queries (using Apache Calcite)

yes

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

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

.NET Client API
HTTP API
LINQ

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C#
Java
PHP

.Net

Server-side scripts

Stored procedures

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

yes

Event Listeners, Executor Services

Transact SQL

yes

Triggers

yes

via the TAP protocol

yes

Events

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

Sharding, horizontal partitioning

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

yes

Replicated Map

yes

Source-replica replication

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

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

depending on model

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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.

Role-based access control

yes

Role based authorization

More information provided by the system vendor

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.