DBMS > Axibase vs. Dgraph vs. Google BigQuery vs. Google Cloud Bigtable vs. Warp 10

System Properties Comparison Axibase vs. Dgraph vs. Google BigQuery vs. Google Cloud Bigtable vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Distributed and scalable native Graph DBMS

Large scale data warehouse service with append-only tables

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

Primary database model

Time Series DBMS

Graph DBMS

Relational DBMS

Key-value store
Wide column store

Time Series DBMS

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

Score	0.32
Rank	#288	Overall
	#25	Time Series DBMS

Score	1.48
Rank	#158	Overall
	#15	Graph DBMS

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	3.58
Rank	#92	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.08
Rank	#358	Overall
	#35	Time Series DBMS

Website

axibase.com/docs/atsd/finance

dgraph.io

cloud.google.com/bigquery

cloud.google.com/bigtable

www.warp10.io

Technical documentation

dgraph.io/docs

cloud.google.com/bigquery/docs

cloud.google.com/bigtable/docs

www.warp10.io/content/02_Getting_started

Developer

Axibase Corporation

Dgraph Labs, Inc.

Google

SenX

Initial release

2013

2016

2010

2015

Current release

15585

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache 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

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Implementation language

Java

Server operating systems

Linux

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

RESTful HTTP/JSON API

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

HTTP API
Jupyter
WebSocket

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Synchronous replication via Raft

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

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

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

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

Atomic single-row operations

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

User concepts

Access control

Planned for future releases

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

Google Cloud Identity & Access Management (IAM)

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

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