DBMS > AnzoGraph DB vs. etcd vs. HBase vs. Heroic vs. RocksDB

System Properties Comparison AnzoGraph DB vs. etcd vs. HBase vs. Heroic vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

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

A distributed reliable key-value store

Wide-column store based on Apache Hadoop and on concepts of BigTable

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Primary database model

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

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

Website

cambridgesemantics.com/anzograph

etcd.io
github.com/etcd-io/etcd

hbase.apache.org

github.com/spotify/heroic

rocksdb.org

Technical documentation

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

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

hbase.apache.org/book.html

spotify.github.io/heroic

github.com/facebook/rocksdb/wiki

Developer

Cambridge Semantics

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Spotify

Facebook, Inc.

Initial release

2018

2008

2014

2013

Current release

2.3, January 2021

3.4, August 2019

2.3.4, January 2021

8.11.4, April 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux

FreeBSD
Linux
Windows

experimental

Linux
Unix
Windows

using Cygwin

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

options to bring your own types, AVRO

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

via Elasticsearch

SQL

Support of SQL

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

APIs and other access methods

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

gRPC
JSON over HTTP

Java API
RESTful HTTP API
Thrift

HQL (Heroic Query Language, a JSON-based language)
HTTP API

C++ API
Java API

Supported programming languages

C++
Java
Python

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Coprocessors in Java

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

yes

Concurrency

Support for concurrent manipulation of data

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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