DBMS > BigObject vs. Datomic vs. DuckDB vs. HugeGraph vs. searchxml

System Properties Comparison BigObject vs. Datomic vs. DuckDB vs. HugeGraph vs. searchxml

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

An embeddable, in-process, column-oriented SQL OLAP RDBMS

A fast-speed and highly-scalable Graph DBMS

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Graph DBMS

Native XML DBMS
Search engine

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

Score	0.13
Rank	#342	Overall
	#150	Relational DBMS

Score	1.76
Rank	#145	Overall
	#66	Relational DBMS

Score	4.68
Rank	#76	Overall
	#41	Relational DBMS

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Score	0.01
Rank	#386	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

bigobject.io

www.datomic.com

duckdb.org

github.com/hugegraph
hugegraph.apache.org

www.searchxml.net/category/products

Technical documentation

docs.bigobject.io

docs.datomic.com

duckdb.org/docs

hugegraph.apache.org/docs

www.searchxml.net/support/handouts

Developer

BigObject, Inc.

Cognitect

Baidu

informationpartners gmbh

Initial release

2015

2012

2018

2015

Current release

1.0.6735, June 2023

0.10, February 2024

0.9

1.0

License

Commercial or Open Source

commercial

free community edition available

commercial

limited edition free

Open Source

MIT License

Open Source

Apache Version 2.0

commercial

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, Clojure

C++

Java

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)

All OS with a Java VM

server-less

Linux
macOS
Unix

Windows

Data scheme

yes

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.

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

RESTful HTTP API

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

Clojure
Java

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

Groovy
Java
Python

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

Lua

yes

Transaction Functions

asynchronous Gremlin script jobs

yes

on the application server

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

yes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

yes

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

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

edges in graph

Transaction concepts

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

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Users, roles and permissions

Domain, group and role-based access control at the document level and for application services

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