DBMS > BoltDB vs. HEAVY.AI vs. Kinetica vs. Titan vs. VoltDB

System Properties Comparison BoltDB vs. HEAVY.AI vs. Kinetica vs. Titan vs. VoltDB

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

An embedded key-value store for Go.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Fully vectorized database across both GPUs and CPUs

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

Primary database model

Secondary database models

Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	0.76
Rank	#224	Overall
	#32	Key-value stores

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	1.46
Rank	#159	Overall
	#74	Relational DBMS

Website

github.com/boltdb/bolt

github.com/heavyai/heavydb
www.heavy.ai

www.kinetica.com

github.com/thinkaurelius/titan

www.voltdb.com

Technical documentation

docs.heavy.ai

docs.kinetica.com

github.com/thinkaurelius/titan/wiki

docs.voltdb.com

Developer

HEAVY.AI, Inc.

Kinetica

Aurelius, owned by DataStax

VoltDB Inc.

Initial release

2013

2016

2012

2010

Current release

5.10, January 2022

7.1, August 2021

11.3, April 2022

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

Apache license, version 2.0

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

C++ and CUDA

C, C++

Java

Java, C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Unix
Windows

Linux
OS X

for development

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C++
Java
JavaScript (Node.js)
Python

Clojure
Java
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Java

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

yes

via pluggable storage backends

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Source-replica replication

yes

Multi-source replication
Source-replica replication

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

none

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

yes

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

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

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

GPU vRAM or System RAM

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

User authentification and security via Rexster Graph Server

Users and roles with access to stored procedures

More information provided by the system vendor

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Related products and services

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More resources

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