DBMS > AnzoGraph DB vs. BigObject vs. BoltDB vs. IRONdb vs. RocksDB

System Properties Comparison AnzoGraph DB vs. BigObject vs. BoltDB vs. IRONdb vs. RocksDB

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Analytic DBMS for real-time computations and queries

An embedded key-value store for Go.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

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

Primary database model

Graph DBMS
RDF store

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Time Series DBMS

Key-value store

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

cambridgesemantics.com/anzograph

bigobject.io

github.com/boltdb/bolt

www.circonus.com/solutions/time-series-database/

rocksdb.org

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.bigobject.io

docs.circonus.com/irondb/category/getting-started

github.com/facebook/rocksdb/wiki

Developer

Cambridge Semantics

BigObject, Inc.

Circonus LLC.

Facebook, Inc.

Initial release

2018

2015

2013

2017

2013

Current release

2.3, January 2021

V0.10.20, January 2018

9.2.1, May 2024

License

Commercial or Open Source

commercial

free trial version available

commercial

free community edition available

Open Source

MIT License

commercial

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++

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

BSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like DML and DDL statements

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

fluentd
ODBC
RESTful HTTP API

HTTP API

C++ API
Java API

Supported programming languages

C++
Java
Python

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

Lua

yes, in Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Automatic, metric affinity per node

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

configurable replication factor, datacenter aware

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

none

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

not needed in graphs

yes

automatically between fact table and dimension tables

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.