DBMS > Machbase Neo vs. SwayDB vs. Titan vs. VoltDB vs. XTDB

System Properties Comparison Machbase Neo vs. SwayDB vs. Titan vs. VoltDB vs. XTDB

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

TimeSeries DBMS for AIoT and BigData

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Titan is a Graph DBMS optimized for distributed clusters.

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

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

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

machbase.com

swaydb.simer.au

github.com/thinkaurelius/titan

www.voltdb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

machbase.com/dbms

github.com/thinkaurelius/titan/wiki

docs.voltdb.com

www.xtdb.com/docs

Developer

Machbase

Simer Plaha

Aurelius, owned by DataStax

VoltDB Inc.

Juxt Ltd.

Initial release

2013

2018

2012

2010

2019

Current release

V8.0, August 2023

11.3, April 2022

1.19, September 2021

License

Commercial or Open Source

commercial

free test version available

Open Source

GNU Affero GPL V3.0

Open Source

Apache license, version 2.0

Open Source

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

Open Source

MIT License

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

Scala

Java

Java, C++

Clojure

Server operating systems

Linux
macOS
Windows

Linux
OS X
Unix
Windows

Linux
OS X

for development

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

only a subset of SQL 99

limited SQL, making use of Apache Calcite

APIs and other access methods

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Java API
JDBC
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Java
Kotlin
Scala

Clojure
Java
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

via pluggable storage backends

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes

Multi-source replication
Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

FOREIGN KEY constraints are not supported

Transaction concepts

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

Atomic execution of operations

ACID

Transactions are executed single-threaded within stored procedures

ACID

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

Snapshots and command logging

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

volatile and lookup table

yes

User concepts

Access control

simple password-based access control

User authentification and security via Rexster Graph Server

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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Recent citations in the news

Titan Graph Database Integration with DynamoDB: World-class Performance, Availability, and Scale for New Workloads
20 August 2015, All Things Distributed

Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database | Amazon Web Services
24 August 2015, AWS Blog

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

5 Q's with Graph Database Expert Marko Rodriguez – Center for Data Innovation
9 November 2013, Center for Data Innovation

DSE Graph review: Graph database does double duty
14 November 2019, InfoWorld

provided by Google News

VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

VoltDB Adds Geospatial Support, Cross-Site Replication
28 January 2016, The New Stack

VoltDB Aims for Fast Big Data Development -- ADTmag
29 January 2015, ADT Magazine

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12 March 2024, Datanami

provided by Google News

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