DBMS > Drizzle vs. Google Cloud Spanner vs. Kinetica vs. searchxml vs. TerarkDB

System Properties Comparison Drizzle vs. Google Cloud Spanner vs. Kinetica vs. searchxml vs. TerarkDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Fully vectorized database across both GPUs and CPUs

DBMS for structured and unstructured content wrapped with an application server

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

Primary database model

Relational DBMS

Native XML DBMS
Search engine

Key-value store

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	2.89
Rank	#105	Overall
	#53	Relational DBMS

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	0.01
Rank	#386	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	0.04
Rank	#377	Overall
	#58	Key-value stores

Website

cloud.google.com/spanner

www.kinetica.com

www.searchxml.net/category/products

github.com/bytedance/terarkdb

Technical documentation

cloud.google.com/spanner/docs

docs.kinetica.com

www.searchxml.net/support/handouts

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Drizzle project, originally started by Brian Aker

Google

Kinetica

informationpartners gmbh

ByteDance, originally Terark

Initial release

2008

2017

2012

2015

2016

Current release

7.2.4, September 2012

7.1, August 2021

1.0

License

Commercial or Open Source

Open Source

GNU GPL

commercial

restricted open source version available

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

C++

C, C++

C++

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux

Windows

Data scheme

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

yes

Query statements complying to ANSI 2011

SQL-like DML and DDL statements

APIs and other access methods

JDBC

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

C++ API
Java API

Supported programming languages

C
C++
Java
PHP

Go
Java
JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

C++

most other programming languages supported via APIs

C++
Java

Server-side scripts

Stored procedures

user defined functions

yes

on the application server

Triggers

hooks for callbacks inside the server can be used.

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication with 3 replicas for regional instances.

Source-replica replication

yes

sychronisation to multiple collections

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

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

GPU vRAM or System RAM

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles on table level

Domain, group and role-based access control at the document level and for application services

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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