DBMS > BoltDB vs. eXtremeDB vs. JanusGraph vs. Oracle vs. RocksDB

System Properties Comparison BoltDB vs. eXtremeDB vs. JanusGraph vs. Oracle vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

Natively in-memory DBMS with options for persistency, high-availability and clustering

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Widely used RDBMS

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Key-value store

Relational DBMS
Time Series DBMS

Graph DBMS

Relational DBMS

Key-value store

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

github.com/boltdb/bolt

www.mcobject.com

janusgraph.org

www.oracle.com/database

rocksdb.org

Technical documentation

www.mcobject.com/docs/extremedb.htm

docs.janusgraph.org

docs.oracle.com/en/database

github.com/facebook/rocksdb/wiki

Developer

McObject

Linux Foundation; originally developed as Titan by Aurelius

Oracle

Facebook, Inc.

Initial release

2013

2001

2017

1980

2013

Current release

8.2, 2021

0.6.3, February 2023

23c, September 2023

8.11.4, April 2024

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

BSD

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 C++

Java

C and C++

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

schema-free

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.

support of XML interfaces available

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

yes

with proprietary extensions

APIs and other access methods

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

C++ API
Java API

Supported programming languages

.Net
C
C#
C++
Java
Lua
Python
Scala

Clojure
Java
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning / sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding, horizontal partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

yes

ACID

isolation level can be parameterized

yes

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

Durability

Support for making data persistent

yes

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

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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