DBMS > Couchbase vs. Heroic vs. JSqlDb vs. OpenQM vs. Splice Machine

System Properties Comparison Couchbase vs. Heroic vs. JSqlDb vs. OpenQM vs. Splice Machine

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded 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

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

JavaScript Query Language Database, stores JavaScript objects and primitives

QpenQM is a high-performance, self-tuning, multi-value DBMS

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Document store

Time Series DBMS

Document store
Object oriented DBMS

Multivalue DBMS

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

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

www.couchbase.com

github.com/spotify/heroic

jsqldb.org (offline)

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

splicemachine.com

Technical documentation

docs.couchbase.com

spotify.github.io/heroic

splicemachine.com/how-it-works

Developer

Couchbase, Inc.

Spotify

Konrad von Backstrom

Rocket Software, originally Martin Phillips

Splice Machine

Initial release

2011

2014

2018

1993

2014

Current release

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

0.8, December 2018

3.4-12

3.1, March 2021

License

Commercial or Open Source

Open Source

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

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

Open Source

AGPL 3.0, commercial license 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.

Implementation language

C, C++, Go and Erlang

Java

Server operating systems

Linux
OS X
Windows

Linux
macOS
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

with some exceptions

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

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

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

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

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

JDBC
Native Spark Datasource
ODBC

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

JavaScript

.Net
Basic
C
Java
Objective C
PHP
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

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

functions in JavaScript

yes

Java

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

none

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

yes

none

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

using RocksDB

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.

Access rights can be defined down to the item level

Access rights for users, groups and roles according to SQL-standard

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