DBMS > Datomic vs. jBASE vs. NSDb vs. Sphinx vs. VoltDB

System Properties Comparison Datomic vs. jBASE vs. NSDb vs. Sphinx vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

A robust multi-value DBMS comprising development tools and middleware

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Open source search engine for searching in data from different sources, e.g. relational databases

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

www.datomic.com

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

nsdb.io

sphinxsearch.com

www.voltdb.com

Technical documentation

docs.datomic.com

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

nsdb.io/Architecture

sphinxsearch.com/docs

docs.voltdb.com

Developer

Cognitect

Rocket Software (formerly Zumasys)

Sphinx Technologies Inc.

VoltDB Inc.

Initial release

2012

1991

2017

2001

2010

Current release

1.0.6735, June 2023

5.7

3.5.1, February 2023

11.3, April 2022

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

Apache Version 2.0

Open Source

GPL version 2, commercial licence available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, Clojure

Java, Scala

C++

Java, C++

Server operating systems

All OS with a Java VM

AIX
Linux
Windows

Linux
macOS

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X

for development

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

full-text index on all search fields

yes

SQL

Support of SQL

Embedded SQL for jBASE in BASIC

SQL-like query language

SQL-like query language (SphinxQL)

yes

only a subset of SQL 99

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

gRPC
HTTP REST
WebSocket

Proprietary protocol

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Clojure
Java

.Net
Basic
Jabbascript
Java

Java
Scala

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Java

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

Using Apache Lucene

yes

The original contents of fields are not stored in the Sphinx index.

yes

Snapshots and command logging

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Access rights can be defined down to the item level

Users and roles with access to stored procedures

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