DBMS > ArcadeDB vs. GeoMesa vs. Google Cloud Bigtable vs. Warp 10 vs. YottaDB

System Properties Comparison ArcadeDB vs. GeoMesa vs. Google Cloud Bigtable vs. Warp 10 vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

A fast and solid embedded Key-value store

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Spatial DBMS

Key-value store
Wide column store

Time Series DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	0.10
Rank	#358	Overall
	#48	Document stores
	#38	Graph DBMS
	#52	Key-value stores
	#35	Time Series DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

arcadedb.com

www.geomesa.org

cloud.google.com/bigtable

www.warp10.io

yottadb.com

Technical documentation

docs.arcadedb.com

www.geomesa.org/documentation/stable/user/index.html

cloud.google.com/bigtable/docs

www.warp10.io/content/02_Getting_started

yottadb.com/resources/documentation

Developer

Arcade Data

CCRi and others

Google

SenX

YottaDB, LLC

Initial release

2021

2014

2015

2001

Current release

September 2021

5.0.0, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

commercial

Open Source

Apache License 2.0

Open Source

AGPL 3.0

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

Scala

Java

Server operating systems

All OS with a Java VM

hosted

Linux
OS X
Windows

Docker
Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language, no joins

by using the Octo plugin

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP API
Jupyter
WebSocket

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

Java

C#
C++
Go
Java
JavaScript (Node.js)
Python

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

depending on storage layer

Internal replication in Colossus, and regional replication between two clusters in different zones

selectable replication factor

based on HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

Atomic single-row operations

optimistic locking

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

Users and groups based on OS-security mechanisms

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

provided by Google News

Time Series Databases Software market latest trends, CAGR, and forecast till 2026 | eSherpa Market Reports
13 April 2020, openPR

provided by Google News

Share this page