DBMS > GeoSpock vs. Lovefield vs. Microsoft Azure Cosmos DB vs. TerarkDB vs. VoltDB

System Properties Comparison GeoSpock vs. Lovefield vs. Microsoft Azure Cosmos DB vs. TerarkDB vs. VoltDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

Embeddable relational database for web apps written in pure JavaScript

Globally distributed, horizontally scalable, multi-model database service

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Relational DBMS

Secondary database models

Time Series DBMS

Spatial DBMS

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

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

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

geospock.com

google.github.io/lovefield

azure.microsoft.com/services/cosmos-db

github.com/bytedance/terarkdb

www.voltdb.com

Technical documentation

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

learn.microsoft.com/azure/cosmos-db

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

docs.voltdb.com

Developer

GeoSpock

Google

Microsoft

ByteDance, originally Terark

VoltDB Inc.

Initial release

2014

2016

2010

Current release

2.0, September 2019

2.1.12, February 2017

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

restricted open source version available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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, Javascript

JavaScript

C++

Java, C++

Server operating systems

hosted

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

tested with Chrome, Firefox, IE, Safari

hosted

Linux
OS X

for development

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

temporal, categorical

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

only a subset of SQL 99

APIs and other access methods

JDBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

C++ API
Java API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

JavaScript

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C++
Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

JavaScript

Java

Triggers

Using read-only observers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

Implicit feature of the cloud service

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

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

yes

Snapshots and command logging

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Access rights for users can be defined per table

Access rights can be defined down to the item level

Users and roles with access to stored procedures

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