DBMS > Altibase vs. CrateDB vs. Google BigQuery vs. LMDB

System Properties Comparison Altibase vs. CrateDB vs. Google BigQuery vs. LMDB

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Distributed Database based on Lucene

Large scale data warehouse service with append-only tables

A high performant, light-weight, embedded key-value database library

Primary database model

Relational DBMS

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	0.71
Rank	#227	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#10	Vector DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Website

altibase.com

cratedb.com

cloud.google.com/bigquery

www.symas.com/symas-embedded-database-lmdb

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

cratedb.com/docs

cloud.google.com/bigquery/docs

www.lmdb.tech/doc

Developer

Altibase

Crate

Google

Symas

Initial release

1999

2013

2010

2011

Current release

v7.3, 2023, August 2023

0.9.32, January 2024

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

commercial

Open Source

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++

Java

Server operating systems

AIX
HP-UX
Linux

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

hosted

Linux
Unix
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, 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

ANSI SQL-92

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

RESTful HTTP/JSON API

Supported programming languages

C
C++
Java

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions (Javascript)

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Configurable replication on table/partition-level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

unique row identifiers can be used for implementing an optimistic concurrency control strategy

Since BigQuery is designed for querying data

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

rights management via user accounts

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

Google Cloud Identity & Access Management (IAM)

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