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DBMS > CrateDB vs. Firebase Realtime Database vs. GridDB vs. LevelDB vs. Vertica

System Properties Comparison CrateDB vs. Firebase Realtime Database vs. GridDB vs. LevelDB vs. Vertica

Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGridDB  Xexclude from comparisonLevelDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionDistributed Database based on LuceneCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Scalable in-memory time series database optimized for IoT and Big DataEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Document storeTime Series DBMSKey-value storeRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSKey-value store
Relational DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#10  Vector DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitecratedb.comfirebase.google.com/­products/­realtime-databasegriddb.netgithub.com/­google/­leveldbwww.vertica.com
Technical documentationcratedb.com/­docsfirebase.google.com/­docs/­databasedocs.griddb.netgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdvertica.com/­documentation
DeveloperCrateGoogle infoacquired by Google 2014Toshiba CorporationGoogleOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20132012201320112005
Current release5.1, August 20221.23, February 202112.0.3, January 2023
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoBSDcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++C++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedLinuxIllumos
Linux
OS X
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampnoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonononono
Secondary indexesyesyesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoSQL92, SQL-like TQL (Toshiba Query Language)noFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
Java
JavaScript
Objective-C
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions (Javascript)limited functionality with using 'rules'nonoyes, PostgreSQL PL/pgSQL, with minor differences
TriggersnoCallbacks are triggered when data changesyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelSource-replica replicationnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyyesACID at container levelnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlrights management via user accountsyes, based on authentication and database rulesAccess rights for users can be defined per databasenofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
CrateDBFirebase Realtime DatabaseGridDBLevelDBVertica infoOpenText™ Vertica™
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
CrateDBFirebase Realtime DatabaseGridDBLevelDBVertica infoOpenText™ Vertica™
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