DBMS > Axibase vs. etcd vs. H2 vs. HugeGraph

System Properties Comparison Axibase vs. etcd vs. H2 vs. HugeGraph

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

A distributed reliable key-value store

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A fast-speed and highly-scalable Graph DBMS

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Website

axibase.com/docs/atsd/finance

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

www.h2database.com

github.com/hugegraph
hugegraph.apache.org

Technical documentation

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

www.h2database.com/html/main.html

hugegraph.apache.org/docs

Developer

Axibase Corporation

Thomas Mueller

Baidu

Initial release

2013

2005

2018

Current release

15585

3.4, August 2019

2.2.220, July 2023

0.9

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache Version 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache Version 2.0

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

Java

Server operating systems

Linux

FreeBSD
Linux
Windows

experimental

All OS with a Java VM

Linux
macOS
Unix

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

also supports composite index and range index

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

gRPC
JSON over HTTP

JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

Java

Groovy
Java
Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

asynchronous Gremlin script jobs

Triggers

yes

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

depending on used storage backend, e.g. Cassandra and HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

depending on used storage backend, e.g. Cassandra and HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Users, roles and permissions

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