DBMS > ObjectBox vs. RisingWave vs. SQLite vs. Stardog vs. Teradata Aster

System Properties Comparison ObjectBox vs. RisingWave vs. SQLite vs. Stardog vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Widely used embeddable, in-process RDBMS

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Platform for big data analytics on multistructured data sources and types

Primary database model

Object oriented DBMS
Vector DBMS

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	0.61
Rank	#237	Overall
	#111	Relational DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Website

github.com/objectbox
objectbox.io

www.risingwave.com/database

www.sqlite.org

www.stardog.com

Technical documentation

docs.objectbox.io

docs.risingwave.com/docs/current/intro

www.sqlite.org/docs.html

docs.stardog.com

Developer

ObjectBox Limited

RisingWave Labs

Dwayne Richard Hipp

Stardog-Union

Teradata

Initial release

2017

2022

2000

2010

2005

Current release

4.0 (May 2024)

1.2, September 2023

3.46.1 (13 August 2024), August 2024

7.3.0, May 2020

License

Commercial or Open Source

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Apache Version 2.0

Open Source

Public Domain

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

C and C++

Rust

Java

Server operating systems

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Docker
Linux
macOS

server-less

Linux
macOS
Windows

Linux

Data scheme

yes

dynamic column types

schema-free and OWL/RDFS-schema support

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes, plus "flex" map-like types

Standard SQL-types and JSON

yes

not rigid because of 'dynamic typing' concept.

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.

Import/export of XML data possible

yes

in Aster File Store

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

APIs and other access methods

Proprietary native API

JDBC
PostgreSQL wire protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

Go
Java
JavaScript (Node.js)
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

UDFs in Python or Java

user defined functions and aggregates, HTTP Server extensions in Java

R packages

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Data sync between devices allowing occasional connected databases to work completely offline

none

Multi-source replication in HA-Cluster

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

yes

Users and Roles

Access rights for users and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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