DBMS > ObjectBox vs. Splice Machine vs. Transwarp Hippo vs. WakandaDB

System Properties Comparison ObjectBox vs. Splice Machine vs. Transwarp Hippo vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Object oriented DBMS
Vector DBMS

Relational DBMS

Vector DBMS

Object oriented DBMS

Secondary database models

Time Series DBMS

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

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS
	#7	Vector DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.05
Rank	#386	Overall
	#16	Vector DBMS

Score	0.10
Rank	#356	Overall
	#17	Object oriented DBMS

Website

github.com/objectbox
objectbox.io

splicemachine.com

www.transwarp.cn/en/subproduct/hippo

wakanda.github.io

Technical documentation

docs.objectbox.io

splicemachine.com/how-it-works

wakanda.github.io/doc

Developer

ObjectBox Limited

Splice Machine

Wakanda SAS

Initial release

2017

2014

2023

2012

Current release

4.0 (May 2024)

3.1, March 2021

1.0, May 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

AGPL 3.0, commercial license available

commercial

Open Source

AGPLv3, extended commercial license available

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++

Java

C++

C++, JavaScript

Server operating systems

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux
OS X
Solaris
Windows

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes, plus "flex" map-like types

yes

Vector, Numeric and 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

SQL

Support of SQL

yes

APIs and other access methods

Proprietary native API

JDBC
Native Spark Datasource
ODBC

RESTful HTTP API

Supported programming languages

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C++
Java
Python

JavaScript

Server-side scripts

Stored procedures

yes

Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

yes

Access rights for users, groups and roles according to SQL-standard

Role based access control and fine grained access rights

yes

More information provided by the system vendor

News

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

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

Evolution of search: traditional vs vector search
23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

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More resources

Recent citations in the news

ObjectBox Raises $2M in Funding
4 December 2018, FinSMEs

The Megashift Towards Decentralized Edge Computing
27 August 2021, hackernoon.com

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ...
19 January 2021, PR Newswire

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

Real-time machine learning with Splice Machine's ML Manager
17 April 2019, TechTarget

How To Axe Db2 But Keep Your Code
10 March 2020, Towards Data Science

provided by Google News

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