DBMS > Apache Doris vs. Derby vs. Google BigQuery vs. KeyDB vs. TempoIQ

System Properties Comparison Apache Doris vs. Derby vs. Google BigQuery vs. KeyDB vs. TempoIQ

Editorial information provided by DB-Engines

Name

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

Description

An MPP-based analytics DBMS embracing the MySQL protocol

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

Large scale data warehouse service with append-only tables

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

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

Primary database model

Relational DBMS

Key-value store

Time Series DBMS

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

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Website

doris.apache.org
github.com/apache/doris

db.apache.org/derby

cloud.google.com/bigquery

github.com/Snapchat/KeyDB
keydb.dev

tempoiq.com (offline)

Technical documentation

github.com/apache/doris/wiki

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

cloud.google.com/bigquery/docs

docs.keydb.dev

Developer

Apache Software Foundation, originally contributed from Baidu

Apache Software Foundation

Google

EQ Alpha Technology Ltd.

TempoIQ

Initial release

2017

1997

2010

2019

2012

Current release

1.2.2, February 2023

10.17.1.0, November 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2

commercial

Open Source

BSD-3

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

Linux

All OS with a Java VM

hosted

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

SQL

Support of SQL

yes

APIs and other access methods

JDBC
MySQL client

JDBC

RESTful HTTP/JSON API

Proprietary protocol

RESP - REdis Serialization Protoco

HTTP API

Supported programming languages

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

user defined functions

in JavaScript

Lua

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

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
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

simple password-based access control and ACL

simple authentication-based access control

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