DBMS > Lovefield vs. Realm vs. TerarkDB vs. TimesTen vs. Vitess

System Properties Comparison Lovefield vs. Realm vs. TerarkDB vs. TimesTen vs. Vitess

Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

In-Memory RDBMS compatible to Oracle

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

google.github.io/lovefield

realm.io

github.com/bytedance/terarkdb

www.oracle.com/database/technologies/related/timesten.html

vitess.io

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

realm.io/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

docs.oracle.com/database/timesten-18.1

vitess.io/docs

Developer

Google

Realm, acquired by MongoDB in May 2019

ByteDance, originally Terark

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

The Linux Foundation, PlanetScale

Initial release

2014

2016

1998

2013

Current release

2.1.12, February 2017

11 Release 2 (11.2.2.8.0)

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

restricted open source version available

commercial

Open Source

Apache Version 2.0, commercial licenses 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

JavaScript

C++

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

Android
Backend: server-less
iOS
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Docker
Linux
macOS

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

with proprietary extensions

APIs and other access methods

C++ API
Java API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

JavaScript

.Net
Java

with Android only
Objective-C
React Native
Swift

C++
Java

C
C++
Java
PL/SQL

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

PL/SQL

yes

proprietary syntax

Triggers

Using read-only observers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

by means of logfiles and checkpoints

yes

In-memory capabilities

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

yes

using MemoryDB

yes

In-Memory realm

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

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More resources

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