DBMS > Couchbase vs. Hazelcast vs. Microsoft Azure Synapse Analytics vs. TimesTen vs. WakandaDB

System Properties Comparison Couchbase vs. Hazelcast vs. Microsoft Azure Synapse Analytics vs. TimesTen vs. WakandaDB

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

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

In-Memory RDBMS compatible to Oracle

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

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	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

www.couchbase.com

hazelcast.com

azure.microsoft.com/services/synapse-analytics

www.oracle.com/database/technologies/related/timesten.html

wakanda.github.io

Technical documentation

docs.couchbase.com

hazelcast.org/imdg/docs

docs.microsoft.com/azure/synapse-analytics

docs.oracle.com/database/timesten-18.1

wakanda.github.io/doc

Developer

Couchbase, Inc.

Hazelcast

Microsoft

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Wakanda SAS

Initial release

2011

2008

2016

1998

2012

Current release

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

5.3.6, November 2023

11 Release 2 (11.2.2.8.0)

2.7.0 (April 29, 2019), April 2019

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

AGPLv3, extended commercial license available

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++

C++, JavaScript

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X
Windows

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.

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

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

SQL-like query language

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

ADO.NET
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

RESTful HTTP API

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

C
C++
Java
PL/SQL

JavaScript

Server-side scripts

Stored procedures

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

yes

Event Listeners, Executor Services

Transact SQL

PL/SQL

yes

Triggers

yes

via the TAP protocol

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

Sharding, horizontal partitioning

none

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

Multi-source replication
Source-replica replication

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

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

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

yes

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

by means of logfiles and checkpoints

yes

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

fine grained access rights according to SQL-standard

yes

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