DBMS > Derby vs. LevelDB vs. PlanetScale vs. TempoIQ

System Properties Comparison Derby vs. LevelDB vs. PlanetScale vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Website

db.apache.org/derby

github.com/google/leveldb

planetscale.com

tempoiq.com (offline)

Technical documentation

db.apache.org/derby/manuals/index.html

github.com/google/leveldb/blob/main/doc/index.md

planetscale.com/docs

Developer

Apache Software Foundation

Google

PlanetScale

TempoIQ

Initial release

1997

2011

2020

2012

Current release

10.17.1.0, November 2023

1.23, February 2021

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

All OS with a Java VM

Illumos
Linux
OS X
Windows

Docker
Linux
macOS

Data scheme

yes

schema-free

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

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

JDBC

ADO.NET
JDBC
MySQL protocol
ODBC

HTTP API

Supported programming languages

Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

yes

proprietary syntax

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

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

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

simple authentication-based access control

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