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

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

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.

RDBMS for high security requirements

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

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Spatial DBMS

Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

arcadedb.com

www.geomesa.org

cloud.google.com/bigtable

linter.ru

www.warp10.io

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

Developer

Arcade Data

CCRi and others

Google

relex.ru

SenX

Initial release

2021

2014

2015

1990

2015

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

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

C and C++

Java

Server operating systems

All OS with a Java VM

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
OS X
Windows

Data scheme

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

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)

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

HTTP API
Jupyter
WebSocket

Supported programming languages

Java

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

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

none

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

Source-replica replication

selectable replication factor

based on HBase

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

yes

Transaction concepts

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

ACID

Atomic single-row operations

ACID

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)

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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