DBMS > AlaSQL vs. AnzoGraph DB vs. ObjectBox vs. Oracle vs. VoltDB

System Properties Comparison AlaSQL vs. AnzoGraph DB vs. ObjectBox vs. Oracle vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

Extremely fast embedded database for small devices, IoT and Mobile

Widely used RDBMS

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store
Relational DBMS

Graph DBMS
RDF store

Object oriented DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

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

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

alasql.org

cambridgesemantics.com/anzograph

objectbox.io

www.oracle.com/database

www.voltdb.com

Technical documentation

github.com/AlaSQL/alasql

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

docs.objectbox.io

docs.oracle.com/en/database

docs.voltdb.com

Developer

Andrey Gershun & Mathias R. Wulff

Cambridge Semantics

ObjectBox Limited

Oracle

VoltDB Inc.

Initial release

2014

2018

2017

1980

2010

Current release

2.3, January 2021

23c, September 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

MIT-License

commercial

free trial version available

Open Source

Apache License 2.0

commercial

restricted free version is available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

JavaScript

C and C++

Java, C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

Linux

Android
iOS
Linux
macOS
Windows

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

Linux
OS X

for development

Data scheme

schema-free

Schema-free and OWL/RDFS-schema support

yes

Schemaless in JSON and XML columns

yes

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

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

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

yes

with proprietary extensions

yes

only a subset of SQL 99

APIs and other access methods

JavaScript API

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

Proprietary native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

JavaScript

C++
Java
Python

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

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++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

PL/SQL

also stored procedures in Java possible

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

none

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication in MPP-Cluster

online/offline synchronization between client and server

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

not needed in graphs

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

isolation level can be parameterized

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

Snapshots and command logging

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'

User concepts

Access control

Access rights for users and roles

yes

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

More information provided by the system vendor

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